HAT2, a HD-ZIP II transcription factor-encoding gene that also acts downstream to auxin response. Our study offers a molecular link between the two major organ maturation factors, CIN-like TCPs and HD-ZIP II transcription factors and explains how TCP activity restricts the cell number and final size in a leaf.Cells in organ primordia undergo active proliferation at an early stage to generate sufficient number, before exiting proliferation and entering differentiation. However, how the actively proliferating cells are developmentally reprogrammed to acquire differentiation potential during organ maturation is unclear. Here, we induced a microRNA-resistant form of TCP4 at various developmental stages of Arabidopsis leaf primordium that lacked the activity of TCP4 and its homologues and followed its effect on growth kinematics. By combining this with spatio-temporal gene expression analysis, we show that TCP4 commits leaf cells within the transition zone to exit proliferation and enter differentiation. A 24-hour pulse of TCP4 activity was sufficient to impart irreversible differentiation competence to the actively dividing cells. A combination of biochemical and genetic analyses revealed that TCP4 imparts differentiation competence by promoting auxin response as well as by directly activating  HAT2 transcription. Our work offers a molecular link between class II TCP and HD-ZIP II genes during the cell differentiation and leaf maturation.Cells in a young organ primordium proliferate to generate sufficient number, before they exit division cycle and enter differentiation programme at later stages. While factors that drive cell cycle progression have been identified and studied in detail in diverse eukaryotic species, developmental factors that promote exit from division and entry into differentiation are less known, especially in the plant kingdom. Here, we show that the class II TCP proteins, notably TCP4, irreversibly reprogram the mitotic cells to exit division and acquire differentiation competence by auxin response as well as direct activation of  Cells in an early organ primordium undergo active proliferation to generate sufficient number, while increasingly more cells exit division cycle and enter differentiation at later stages of organ growth, thus ensuring a mature organ with defined size ,2. WhileEarly leaf growth is sustained by cell division and mitotic cell expansion, collectively referred to as proliferation, which takes place throughout the primordium. As the primordium increases in size, the domain of this proliferation zone increases initially and is then maintained at constant size . As cellTEOSINTE BRANCHED 1, CYCLOIDEA, PROLIFERATING CELL FACTOR1/2) transcription factors [Cell number in a mature leaf depends on the size of the proliferation zone, the rate of proliferation within it and the rate at which cells exit proliferation and enter differentiation within the transition zone; perturbation in any of these parameters leads to altered cell number and final leaf size ,11. Many factors –18.TCP genes are predicted to encode non-canonical, basic helix-loop-helix transcription factors [jaw-D plants where the level of these five TCP transcripts are reduced due to the overexpression of endogenous miR319a, leaf size is increased as a result of excess number of pavement cells, whereas leaves with elevated level or activity of these TCP proteins are smaller in size with reduced cell number due to precocious differentiation [The  factors ,20 that  factors . Five mi factors ,14,15. Intiation ,22,23. Bntiation . HoweverYUCCA1, 4 and 6, suggesting that TCP15 is a negative regulator of auxin biosynthesis [IAA3 (INDOLE-3-ACETIC ACID INDUCIBLE3)/ SHY2 (SHORT HYPOCOTYL2), a negative regulator of auxin signaling, and PIN1 (PIN-FORMED1), 5, 6, AUX1 (AUXIN RESISTANT1), the polar auxin transporters [YUC5, an auxin biosynthetic gene [TCP-mediated cell differentiation and organ maturation has been linked to the biosynthesis and response pathways of the major phytohormone, auxin . Auxin cynthesis . Similarsporters ,26. By ctic gene . Even thHD-ZIP genes during leaf morphogenesis. In addition, some members of the class II HD-ZIP genes, specifically HAT1/2, are activated by auxin response and promote cell expansion and organ maturation [HAT1 or HAT2 produce smaller leaves with reduced cell number and elongated hypocotyl cells [TCP genes [The role of the plant-specific homeodomain-leucine zipper (HD-ZIP) transcription factors has been implicated in leaf morphogenesis. The HD-ZIP members are classified into four sub-groups (I to IV) based on sequence similarity within the DNA-binding homeodomain ,29. Functuration ,34,37,38CP genes ,23,27. HHAT2 transcription by TCP4.Here, we induced a dominant form of TCP4 protein at various developmental stages of Arabidopsis leaf primordium that lacked class II TCP function and followed its effect on leaf growth kinematics. By combining this with spatio-temporal expression of endogenous TCP4, we show that the class II TCP proteins irreversibly reprogram the mitotic cells to exit division and acquire differentiation competence within the transition zone. Induction of cell maturation is mediated by auxin response as well as by direct activation of TCP genes are heterochronic regulators of leaf development and their function has been implicated in the repression of cell division [TCP genes–TCP2, 3, 4, 10 & 24—in cell division/ differentiation of Arabidopsis leaves, we compared the mature first leaf pair and their epidermal cells of wild type (Col-0) with those in the loss-of-function mutants tcp2;4;10 [jaw-D, where all the five TCP transcripts are down-regulated due to the over-expression of miR319a [tcp2;4;10 and jaw-D leaves measured >1.5 times larger than the Col-0 leaves  showed smaller leaves with reduced cell number  compared to the mock treatment, demonstrating that TCP4 is a strong cell proliferation inhibitor. Similar negative effect of TCP4 on leaf size and cell number was also observed in three independent transgenic lines where three different gain-of-function forms of TCP4 were expressed constitutively under a leaf primordia-specific promoter (ProBLS:rTCP4:GFP) [Pro35S:TCP4:3F6H) [ProTCP4:TCP4:VP16) [The class II division  and the division . In ordecp2;4;10  and jaw- miR319a . The tcp0 leaves , as was 0 leaves , suggestd Pro35S . DEX-grol number . A more l number  and celll number  were obsCP4:GFP) , a ubiquP4:3F6H)  or the eP4:VP16)   showed no effects on leaf size, cell number and pavement cell area , during which the average area of the abaxial pavement cells remained small (~500 μm2 or less) and their number increased exponentially , exponential (10–18 DAS) and saturating (18–22 DAS) phase. However, the jaw-D blades started expanding at a rate faster than that of Col-0 from the earliest stage measured  in both the genotypes, resulting in ~2.5 times more cells in the mature jaw-D leaf compared to Col-0  and then increased exponentially until 16 DAS, before saturating rather abruptly  as in Col-0, but at a slower rate, resulting in fewer cells at maturity compared to Col-0  and larger (>3000 μm2) pavement cells in expanding Col-0 lamina (jaw-D. During early growth (6–8 DAS), nearly all Col-0 pavement cells measured <1500 μm2, and their proportion sharply declined to ~30% at 22 DAS as the blade expanded , a measure of leaf maturation , in the jaw-D;GR rosette leaves were smaller with smoother margin when grown with continuous presence of DEX  of the average area 2920 ± 140 μm2. The blade area progressively increased from 12.0 ± 1.7 mm2 to the non-inductive value of 32.6 ± 2.5 mm2 when TCP4 was induced at 4, 5 or 6 DAS, even though their final cell numbers were much fewer than the non-inductive value. When TCP4 was induced at 6 DAS, its blade area at maturity was close to the jaw-D value (30.4 ± 2.3 mm2), even though its cell number was almost half of that in jaw-D leaf (2)  .jaw-D;GR blade area progressively increased to a maximum of 46 mm2, nearly 1.5-fold bigger than the jaw-D blade  were larger than the jaw-D cells (1870 ± 170 μm2), ultimately yielding a mature leaf that was bigger than even the jaw-D leaf. It may be noted here that the jaw-D leaves were at the peak of its exponential phase of proliferation at 10 DAS, when almost all pavement cells were smaller in size  and 12.7 ± 1.0 mm2  upon continuous TCP4 induction , when the average length of leaf primordium was 274 ± 35 μm  with a 24-hour pulse. This suggests that TCP4 activity for the duration of 24 hours is sufficient to impart commitment to differentiation in a dividing cell. Consequently, a 24-hour DEX pulse at 4, 6, 8, 9, 10 and 12 DAS  and 8C (1.7%) nuclei decreased, suggesting a less differentiation status of this cell population. Conversely, when TCP4 function was induced in these leaves, the fraction of 2C nuclei reduced to 34.8%, with a concomitant increase in the proportion of 4C (55.7%) and 8C (9.5%) nuclei. Together these results demonstrate that TCP4 makes the proliferative cells exit division cycle and enter into endoreplication.Increased cell maturation upon TCP4 induction was also reflected in the elevated level of nuclear ploidy, a typical cell differentiation marker , in cellTCP module with their expression dynamics in expanding leaf blade, we localized miR319c and TCP4 promoter activity and TCP4 protein at various growth stages of transgenic leaves expressing GUS reporter. In a 19-day old ProTCP4:GUS seedling, strong GUS activity was detected throughout the blade of the 9th rosette leaf (1.2 mm long), which was progressively restricted towards the proximal end in the more mature 8th, 7th and 6th leaves  of PromiR319c:GUS seedlings (th leaf (1.9 mm long); no detectable GUS activity was found in the 7th and the 6th leaves. These results are in agreement with the earlier reports [miR319c promoter is active during a small temporal window at the earliest stage of leaf growth. Consequently, the TCP4:GUS reporter activity in young ProTCP4:TCP4:GUS leaf at the 9th position was not detected in the corresponding basal region where miR319c promoter is active at this stage, suggesting that miR319 activity excludes TCP4 transcript [GUS reporter was detected in a small domain at the base of the young 9eedlings , and exp reports , and suganscript  and its TCP4 transcript and TCP4 protein in young leaf primordia where miR319 promoter is active, we studied the GUS expression pattern in 4-day old transgenic seedlings where the first leaf pair just initiated , barely detectable TCP4:GUS activity was found towards the distal extreme , implyinr length . At a laundaries , which heedlings , highligYUCCA5 (YUC5), a known differentiation marker [ProYUC5:GUS seedlings, and the expression extended towards more proximal direction as the leaf matured , where cells are insensitive to auxin response due to the sequestration of AUXIN RESPONSE FACTORs (ARF6 and 8) by a dominant, non-degradable form of AUX/INDOLE-3-ACETIC ACID3 (IAA3) inhibitor protein [jaw-D;GR X Col-0 heterozygous seedlings grew to 29 ± 2.6 mm2, consisting of 18850 ± 1670 pavement cells with average area of 1550 ± 165 μm2  and <10% cells of larger area (>3000 μm2). Upon TCP4 induction, the fraction of the smaller cells decreased to ~25% and that of larger cells increased to ~50% in jaw-D;GR X Col-0, indicating a rescue of the cell size defect by TCP4 activity. The extent of rescue was, however, less  in the jaw-D;GR X shy2-2 leaves, suggesting that TCP4 partly requires auxin response to induce cell maturity.The pavement cell population of the mature ondition , with ~7HAT2 and its closest homologue HAT1 have been recognized as immediate auxin responsive genes and control cell proliferation in leaves and cell elongation in hypocotyls, functions that overlap with miR319-targeted TCP genes [HAT1 and HAT2 transcripts were consistently up-regulated in multiple independent microarray datasets performed upon external auxin application ; two in the promoter region and the third in the coding region  assay in the Pro35S:TCP4:3F6H transgenic line using anti-FLAG antibody [HAT2 upstream regulatory regions that corresponded to the TCP4 binding motifs  experiment [HAT2 chromatin assumed more open conformation in the regions corresponding to the putative TCP4-binding sites and not in a distant region when TCP4 was activated in the Pro35S:mTCP4:GR seedlings by dexamethasone treatment . However, this line reduced the size of the jaw-D leaf by ~30% and its pavement cell number by ~50%  [HAT1 is a strong cell proliferation inhibitor in developing leaves. Moreover, HAT1 overexpression rescued the effect of class II TCP down-regulation on the leaf size and pavement cell number of the jaw-D;GR leaves nearly to the Col-0 values  is likely to be an indirect target of TCP4 as it is an auxin response gene (YUC5 activation (HAT1 and HAT2) rescued jaw-D phenotype . 12 μM DEX was used for TCP4 induction in all the experiments unless specified otherwise.Col-0 was used as the wild type control in all experiments. The mutant lines eviously ,15,33,55reported . The homeviously ,59,67,68TCP4 including 5’ untranslated region was amplified using the forward primer 5’-AATTGACCCTTTTCTATCATGC-3’ and the reverse primer 5’-TGGTAGAGCATATTCGTCGAGA-3’, pfu DNA polymerase and Col-0 genomic DNA and cloned into pGEMT-Easy vector by TA cloning  [pCAMBIA 1304 using NcoI and SacI digestion to generate ProTCP4:GUS construct.The 2.16 kb upstream region of ProTCP4)  and thenTCP4 cDNA fragment of pBSKS-TCP4:GR [pCAMBIA-1391Xa to generate TCP4:GUS cassette. The NotI released 2.16 kb ProTCP4 fragment of pGEMT-Easy-ProTCP4, described above, was end filled with Klenow DNA polymerase and cloned upstream of the TCP4:GUS cassette by blunt end ligation to generate ProTCP4:TCP4:GUS construct. The transgenic lines were generated in Col-0 background by Agrobacterium tumefaciens-mediated floral dip method [The -TCP4:GR  was digep method .rsbweb.nih.gov/ij/). The first leaf from 29-day old plants were cleared with 70% alcohol and processed in choral hydrate:water:glycerol (8:2:1) solution and lactic acid for one to three weeks. In another method, leaves were collected in 70% ethanol followed by shifting them to ethanol:glacial acetic acid (7:1) and kept overnight (12–14 h) at room temperature. After clearing, the leaf tissues were treated with 1 M KOH for maximum 30 min in constant rotating followed by two times washing with double-distilled water. Image of abaxial epidermal cells were taken using differential interference contrast microscope  and analyzed with Image J software. For cell size analysis, 400–750 cells area was measured from different fields of 4–7 leaves and averaged to obtain the final cell size. The total number of cells per leaf was calculated by using the average cell size and leaf area.For the measurement of leaf size the crinkled leaves were flattened and photographed using a Canon PowerShot S110 camera. Leaf area measurement was made in the photographs using Image J software  method after treatment with ethanol solvent (Mock) or 12 μM dexamethasone. To check the relative expression of respective genes, quantitative RT-PCR was performed using SYBER Green qPCR kit  according to the manufacturer’s instructions. Results were analyzed using ABI Prism 7900HT SDS software  and ΔΔCT values were determined after normalization with internal control. Intensity ratios were calculated using the formula 2 earlier ,70. GUS  earlier . The lisst pair of leaves from 8-day old seedlings of indicated genotypes were collected after removing hypocotyl and cotyledons. Ploidy levels were measured using the protocol provided earlier [2, 30 mM sodium citrate, 20 mM 4-morpholinepropane sulfonate, and 1% Triton X-100, pH 7.0) and finely chopped using sharp razor blade followed by homogenizing in the buffer. The homogenate was filtered through Miracloth (22–25 μm) and treated with 10 μl/ml RNaseA (1mg/ml stock) for 20–30 min followed by nuclear DNA staining with 50 μl/ml of propidium iodide (1 mg/ml stock) and kept in dark at 4°C for 30 min. Samples were run through BD FACS verse (USA) flow cytometer and analyzed using BD FACS unit software. It was considered that the left-most peak corresponds to 2C [1 earlier ,72. In bds to 2C ,72Pro35S:TCP4:3F6H seedlings were harvested and crushed into fine powder in liquid nitrogen. The powder was homogenized in the nuclei extraction buffer 1  and proceeded for cross-linking. 37% formaldehyde was used for crosslinking by gentle rotating in 4°C for 10 min and 2 M glycine was added to stop the reaction. After quenching the cross-linked samples were filtered through two layers of Miracloth and centrifuged for 10 min at 10 k rpm at 4°C. The pellets containing the nuclei were resuspended and washed twice with extraction buffer 2  Triton X-100, 5 mM β-mercaptoethanol, 0.1 mM PMSF, 1 mM Na3VO4, 1 mM NaF, and Complete protease inhibitor cocktail tablets) and transferred to ice-cold 1.5mL Eppendorf tubes followed by centrifugation at maximum rotor speed for 10 min at 4°C to isolate the nuclei. The isolated nuclei were lysed using Nuclei lysis buffer  and proceeded for sonication to shear the chromatin (~ 500 bp to 1 kb size fragments) using Bioruptor . The sheared chromatin were diluted in ChIP dilution buffer  to make the volume up to 1.5 mL and centrifuged at maximum speed for 5 min at 4°C. From the collected chromatin solution, 30 μL (2%) was kept as input for the assay and rest of the solution was divided into two parts from which one was immunoprecipited using anti-FLAG antibody  and the other using Anti-IgG antibody . Magnetic Dynabeads Protein G (Life technologies) were used for Immunoprecipitation for which first the beads were pretreated with the anti-FLAG antibody  or anti-IgG antibody for 20 min by rotating at room temperature and diluted in ChIP dilution buffer after washing twice with 1X PBST. The antibody-bound beads were incubated with chromatin solution (26 μL Dynabeads and 3 μL antibody per 600 μL of chromatin solution) for 20 min in ice followed by 2 h rotating at 4°C. After immunoprecipitation, the immunocomplex was washed using low salt buffer  and high salt buffer  and TE buffer . To elute the immunocomplex from the beads, 50 μL of nuclei lysis buffer was added and incubated for 20 min at 65°C and the elution was repeated twice. Eluted immunocomplex along with the input samples were reverse cross-linked by adding 6 μL of 5 M NaCl and incubating at 65°C overnight. Proteinase K and RNase A was treated to digest all proteins and RNA, respectively, and finally DNA were cleaned up by phenol:chloroform:isoamyl alcohol (15:24:1) followed by precipitation using sodium acetate and 100% ethanol. The final extracted DNA was dissolved in 50 μL of nuclease-free water and proceeded for qPCR using 0.8 μL DNA as template per reaction.ChIP protocol was followed as mentioned earlier . In brie(Ct input- Ct IP) X 100 and normalized to IgG control. The final fold enrichment was plotted in relative to Col-0 value.To quantify the relative enrichment on the respective gene element, qPCR was performed using 0.8 μL of immunoprecipited DNA and SYBER Green qPCR kit  in a 10 μL reaction volume according to manufacturer’s protocol. Relative enrichment was calculated using the formula 0.02 X 2S1 FigPro35S:mTCP4:GR #2 plants grown in the absence (Mock) or presence (DEX) of 12 μM dexamethasone. (B) Level of TCP4 transcript (relative to PP2A) in 9-day old seedlings of indicated genotypes analyzed by RT-qPCR. Averages of three biological replicates are shown. (C) to (E) Averages of leaf area (C), cell number (D) and abaxial pavement cell size (E) of leaves shown in (A). Sample number, 20. (F) to (K) Mature first leaves (F) collected from 29-day old plants, their area (G), total cell number (H), relative cell number reduction to Col-0 (I), abaxial pavement cell size (J) and relative cell area to Col-0 (K). Sample number, 8 to 12 leaves. Error bars indicate SD. * indicates p <0.05. Unpaired Student’s t-test was used. For (E) and (J), 120–140 cells per leaf were measured and averages of 3–4 leaves are shown. Scale bars in , 2.5 mm.(A) Mature first leaves from 29-day old (TIF)Click here for additional data file.S2 FigProTCP4:mTCP4:GR and jaw-D;ProTCP4:mTCP4:GR plants relative to the mock-treated values. (C) Frequency distribution of abaxial pavement cell size in the first leaf shown in (A). Total 120–150 cells per leaf were measured and averages from 5 leaves are shown. (D) Frequency distribution of pavement cell size on the abaxial surface of mature first leaf from Col-0;ProTCP4:mTCP4:GR plants grown in the absence (Mock) or presence (DEX) of dexamethasone. Error bars indicate SD. * indicates p < 0.05. Unpaired Student’s t-test was performed. Scale bars, 100 μm (A).(A) Outline of epidermal cells on the abaxial surface of mature first leaf. (B) Area of pavement cells in mature first leaves from DEX-treated Col-0;(TIF)Click here for additional data file.S3 Figjaw-D;ProTCP4:mTCP4:GR plants grown in the absence (Mock) or presence (DEX) of 12 μM dexamethasone. (B) Schematic of a leaf (left) to highlight the region on the abaxial surface (yellow square) used for cell size analysis and morphology of epidermal cells on the abaxial surface of the first leaf pair of Col-0 in the corresponding regions at two different growth stages (right). (C) to (E) Proportion of smaller (<1500 μm2) and large (>1500 μm2) cells on the abaxial surface of first leaf at different days after stratification in Col-0 (C) plants and jaw-D;ProTCP4:mTCP4:GR  plants grown in the absence  or presence  of dexamethasone. N, 10–13 leaves. For each time point, total 30–40 cells per leaf at specified region shown in (B) were measured and averages from 5–7 leaves shown. Error bars indicate SD.(A) Average width of the first leaf pair of Col-0 and (TIF)Click here for additional data file.S4 Figjaw-D;ProTCP4:mTCP4:GR plants by shifting the seedlings from Mock→DEX (A) or DEX→Mock (B) at indicated days after stratification (DAS). All the leaf parameters shown in (A) and (B) TCP4 function was induced in the (TIF)Click here for additional data file.S5 Figjaw-D;ProTCP4:mTCP4:GR seedlings grown in the absence of dexamethasone and then shifted to dexamethasone-containing medium at 8 or 10 days after stratification (DAS) and size of their pavement cells on the abaxial surface (B). N, 12–15 leaves. For each time point, total 30–40 cells per leaf at specified region , Col-0;Pro35S:mTCP4:GR  and Col-0;Pro35S:TCP4:GR  plants treated with 12 μM dexamethasone for 48 hours at indicated days after stratification (DAS). Plants grown in continuous absence  or presence  of dexamethasone are shown as controls. Dotted lines indicate the values corresponding to Mock. N, 10–15 leaves. Error bars indicate SD.(A) and (B) Average area (A) of the first leaf from d region  were mea(TIF)Click here for additional data file.S6 Figjaw-D;ProTCP4:mTCP4:GR plants by shifting the seedlings from Mock→DEX for 24 hours at indicated days after stratification (DAS) and then again to Mock condition. Mature first leaf size was analyzed at 29 DAS.Pulse of dexamethasone treatment was performed in the (TIF)Click here for additional data file.S7 FigPro35S:mTCP4:GR #2 plants grown either in the total absence of dexamethasone (Mock) or in the presence of 12 μM dexamethasone (DEX) for the indicated number of days and then shifted to Mock till 29 DAS. (B) Average area (N = 10–15) of leaves shown in (A). The dotted line is drawn through the Mock value parallel to the X-axis.(A) Mature first leaves of 29-day old (TIF)Click here for additional data file.S8 FigGUS reporter analysis of the first leaf pair in 4-day old seedlings grown in the absence of dexamethasone. All genotypes were analyzed in the F1 generation. Numbers indicate leaf length in mm.(TIF)Click here for additional data file.S9 Fig(TIF)Click here for additional data file.S10 FigHAT2 upstream regulatory regions (R1-R3 shown in Pro35S:mTCP4:GR seedlings before (Mock) or after (DEX) 12 μM dexamethasone treatment for 4 h. YUC5 was used as a positive control [TA3. Averages of biological triplicates are shown. Error bars indicate SD. ns, not significant, * indicates p <0.05, unpaired Student’s t-test was used. (B) A schematic representation of HAT1 genomic structure. Exons are shown in gray boxes and the translation start site is shown by an arrow. Two putative TCP4 DNA-binding motifs (TGGCCC) are indicated. The four regions used for the ChIP-qPCR amplification (in C) are shown as R1-R4. (C) ChIP-qPCR analysis of HAT1 locus (R1-R4 in B) with anti-FLAG antibody. LOX2 and TUB2 were used as positive and negative controls, respectively (shown in HAT2 ChIP experiment). Averages of biological triplicates of qPCR analysis are shown.(A) Quantitative PCR analysis of the  control  and R3 s(TIF)Click here for additional data file.S11 FigTCP4, HAT1 and HAT2 transcripts at various developmental stages as analyzed by Genevestigator tool (https://genevestigator.com/gv/doc/intro_plant.jsp) (A) and estimated by RT-qPCR (B). For (B), RNA samples were isolated from seedlings  and from first pair of leaves . PP2A was used as an internal control. Error bars indicate SD.(A) and (B) Levels of (TIF)Click here for additional data file.S12 Figjaw-D;GR and JAB:GFP indicate jaw-D;ProTCP4:mTCP4:GR and Pro35S:JAB:GFP, respectively. For (F) total 125–150 cells per leaf were measured and averages from 3–7 leaves shown. Error bars indicate SD. * indicates p <0.05. Unpaired Student’s t-test was used.(A) to (F) 30-day old first leaves (A), their average area (B), total pavement cell number (C), cell number relative to Col-0 (D), outline of abaxial pavement cells (E) and their average area (F). N, 8–12 leaves. (TIF)Click here for additional data file.S1 Table(XLSX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.


Background: Although there is evidence that the CYP3A4*22 variant should be considered in tacrolimus dosing in renal transplantation, its impact beyond tacrolimus dose requirements remains controversial.Methods: In a cohort of 121 kidney transplant recipients, we analyzed the CYP3A4*1B, CYP3A4*22, and CYP3A5*3 alleles and the ABCB1 variants 1236C>T, 2677G>T/A, and 3435C>T for their impact on exposure and dose requirement. Relevant clinical outcome measures such as acute rejection within the first year after transplantation, delayed graft function, and renal function at discharge (estimated glomerular filtration rate) were evaluated.Results: Extensive metabolizer  showed significantly higher tacrolimus dose requirement (P = 0.004) compared with both intermediate metabolizer , and poor metabolizer  after onset of therapy. Significantly higher dose requirement was observed in CYP3A5 expressers (P = 0.046) compared with non-expressers again at onset of therapy. Using the log additive genetic model, the area under the curve for the total observation period up to 16 days was significantly associated with the CYP3A5*3 genotype (P = 3.34 × 10-4) as well as with the IM or extensive metabolizer phenotype (P = 1.54 × 10-4), even after adjustment for multiple testing. Heterozygous carriers for CYP3A4*22 showed significantly higher areas under the curve than the CYP3A4*1/*1 genotype in the second week post-transplantation (adjusted P = 0.016). Regarding clinical outcomes, acute rejection was significantly associated with human leukocyte antigen mismatch . Graft recipients from deceased donors showed higher incidende of delayed graft function  and a lower estimated glomerular filtration rate at discharge (P = 0.0001). Tested CYP3A4 or CYP3A5 variants did not show any effects on clinical outcome parameters. ABCB1 variants did neither impact on pharmacokinetics nor on clinical endpoints.Conclusion: At our transplantation center, both CYP3A5*3 and, to a lesser extent, CYP3A4*22 affect tacrolimus pharmacokinetics early after onset of therapy with consequences for steady-state treatment in routine clinical practice. Streptomyces tsukubaensis, is an inhibitor of T cell proliferation widely used in solid organ transplantation. After kidney transplantation, it is part of the maintenance immunosuppressive regimen including mycophenolic acid and corticosteroids , but the frequency distribution of these variants is usually very low, and functional consequences are missing. However, the CYP3A4*22 allele, an intronic base change from G to A (rs35599367), has been recently correlated with reduced expression of the CYP3A4 enzyme ] is still a matter of discussion. AR is regarded as one of the strongest predictors of allograft survival and thus a clinically critical outcome parameter . A meta-tigation . The abs4 enzyme  and asso4 enzyme .0) even after including CYP3A5 genetics is not sufficiently explained as well. For several variants in drug-metabolizing enzymes or transporters, significant associations with tacrolimus C0 levels have been reported. However, in a validation study, a panel of 44 variants in selected candidate genes associated with tacrolimus pharmacokinetics was investigated, and variants in CYP3A5 (including others that are in strong linkage disequilibrium with CYP3A5*3) and the CYP3A4*22 allele hold true for validation  found an additional association of the CYP3A4*22 allele with tacrolimus C0 levels , and renal function upon discharge. We report on 121 kidney transplant recipients whose tacrolimus levels have been closely monitored in the early period after transplantation. In addition to the CYP variants, we selected three polymorphisms of ABCB1 (encoding P-glycoprotein), since contradictory data regarding tacrolimus pharmacokinetics and ABCB1 genetics in renal transplant patients  status, antiviral prophylaxis with valgancyclovir is administered only to CMV-negative recipients receiving a CMV positive graft. Demographic characteristics of the study cohort are shown in Data from 121 patients who underwent kidney transplantation between 2009 and 2015 at the Transplantation Center of Klinikum Stuttgart, Germany, were available for analysis. The study was approved by the ethics committee of University Hospital, Tuebingen, Germany (616/2013BO2). All patients signed a written informed consent. As induction therapy, 86% (104/121) of kidney transplant recipients received the interleukin-2 receptor antagonist basiliximab, while the remaining 14% received thymoglobulin due to high immunologic risk. The immunosuppressive maintenance therapy after renal transplantation at the transplantation center at Klinikum Stuttgart, Germany is a triple therapy of tacrolimus, mycophenolate mofetil, and prednisolone. Tacrolimus therapy is started at the day of renal transplantation with a dosage of 0.1 mg/kg/day orally and subsequently adjusted to achieve a target tacrolimus CCYP3A4*1B (rs2740574), CYP3A4*22 (rs35599367), and CYP3A5*3 (rs776746) and the three most relevant ABCB1 variants 1236C>T (rs1128503), 2677G>T,A (rs2032582), and 3435C>T (rs1045642). Genotyping was performed using TaqMan assays on 7900HT Fast Real-Time PCR System and the allelic discrimination method according to the manufacturer’s instructions . CYP3A4*1: assay C___1837671_50; CYP3A4*22: assay C__59013445_10; CYP3A5*3: assay C__26201809_30; ABCB11236C>T, assay C___7586662_10; triallelic ABCB12677: assays C_11711720D_40  and C_11711720C_30 ; ABCB13435C>T: assay C___7586657_20).Genomic DNA was isolated from 200-µl ethylenediaminetetraacetic acid whole blood using QIAamp DNA Blood Mini Kit  according to the manufacturer’s protocol. For genotyping, the following variants were selected: CYP3A4/5 genotypes were defined as follows: poor metabolizers , intermediate metabolizer , and extensive metabolizer .As described previously , the com0 (nanogram per milliliter) available from the first 2 weeks after transplantation or until the patient was discharged were retrospectively gathered from patient files. Tacrolimus concentrations are measured in whole blood by a validated liquid chromatography with tandem mass spectrometry as a routine laboratory procedure . Area under the time–concentration curve (AUC) was used as an estimate of the exposure to tacrolimus over time, since C0 was not available at every single postoperative day for every patient. Separate calculations were made for the first week (AUC1–7days), the second week (AUC8–14days), and for the whole follow-up period (AUC1–16days). AUC is reported as tacrolimus concentration divided by daily dose times days, i.e. (ng/mL)/ (mg/day) × days.Trough concentrations Crocedure . Dose-adClinical outcome measures for this study were AR, DGF, and renal function at discharge from the hospital. AR was defined as an acute deterioration in allograft function associated with specific pathologic changes in graft biopsies occurring during the first year after transplantation. DGF was defined as the need for dialysis within the entire 16 days post-transplantation for this study. Estimated glomerular filtration rate based on serum creatinine (eGFR) was used as measure for renal function at discharge from the hospital.ABCB12677G>T/A variant, the HWTriExact function from the R-package HardyWeinberg_v.1.6.1 was used  among individuals with different genotypes were investigated using Kruskal–Wallis tests, Wilcoxon–Mann–Whitney tests, or median regression as appropriate. The variants were considered in four different genetic models: codominant, dominant, recessive, and log additive. For the tri-allelic ABCB1 2677G>T,A variant, T and A allele were combined before applying these models.AUC values were estimated from the available individual CThese models were also applied for the multivariate logistic/linear regression analyses of genetic variants and their association with AR, DGF, or square root transformed eGFR. Here, human leukocyte antigen (HLA) mismatch (≥3 vs <3), panel reactive antibodies (>10% vs ≤10%), AB0 compatibility, (yes vs no), donor source (living vs. deceased), type of agent used for induction (basiliximab vs. thymoglobulin), previous transplantation (yes vs. no), and valgancyclovir therapy (yes vs. no) were considered as covariates. The association of AR, DGF, and eGFR with confounders was tested with Fisher tests; for the continuous variable eGFR, Wilcoxon rank sum tests were employed.Post hoc power calculation was performed based on a two-sample t-test, the respective effect and samples sizes in our cohort, and a two-sided significance level of 5%. Weight-adjusted doses at day 10 were log-transformed in order to estimate coefficients of determination based on univariate linear models.All statistical tests were two-sided, and significance level was set to 5%. Where indicated, P-values were adjusted for multiple testing according to CYP3A4 variants *1B and *22 were not linked . There were no homozygotes for the CYP3A4*22 allele, and 9.9% were heterozygous carriers. The minor allele frequency for CYP3A4*22 was 5%. Seventeen patients were heterozygous carriers for CYP3A5*1, and one patient carried two functional alleles (*1/*1). In total, 11 patients (8.7%) were classified as PM , 93 patients (77.0%) as IM , and 17 patients (14.3%) as EM . For the ABCB1 variants, linkage was observed between 1236C>T and 2677G>T , 1236C>T and 3435C>T , as well as 2677G>T and 3435C>T . LD plots with D’ and r2 are shown in All genotype frequencies were in Hardy–Weinberg equilibrium. The two CYP3A5 allele, n = 18) was observed compared with non-expressers . This association remains significant for the total observation period of 16 days. These data are also supported by a significantly higher dose requirement (P = 0.004) for EM (n = 17) patients compared with both IM (n = 93) and PM (n = 11) subjects for the entire observation period. A trend of significance toward a decreased dose requirement in heterozygous CYP3A4*22 patients was evident after the first week of therapy, being statistically significant at day 10 (P = 0.03). A post hoc power calculation for CYP3A4*22 showed a power of 63.5%. Here, we used the data at day 10 after transplantation; a dose/weight showed a plateau after this time point. Moreover, based on univariate linear models with log-transformed weight-adjusted doses, estimated coefficients of determination were 2.7% for CYP3A4*1B, 4.8% for CYP3A4*22, 18.7% for CYP3A5*3, and 21.2% for the CYP3A4/5 combined genotypes. In addition, carriers of CYP3A4*1B showed a significant higher tacrolimus dose requirement after day 12 of treatment (p = 0.026), keeping in mind that CYP3A4*1B and CYP3A5*3 are in strong linkage disequilibrium . None of the selected ABCB1 variants showed significant effects on the tacrolimus dose requirement.As illustrated in CYP3A5*3/*3 had significantly increased AUCs calculated from the C0 measurements compared with CYP3A5 expressers even after consideration of multiple testing . In the same timeframe, significant increased AUCs were found in PM and IM compared with EM . Heterozygous carriers of the CYP3A4*22 variant showed significantly higher median AUCs from days 8–14 (log additive model: adjusted P = 0.016), while for the entire study period of 16 days, only a trend of significance was found (adjusted P = 0.176). Results for the tested CYP3A4 and CYP3A5 variants are shown in CYP3A4*1B and variants of ABCB1 , no significant effects on the AUC of dose-adjusted tacrolimus concentrations were revealed. An overview of the distribution of median tacrolimus levels for the entire observation period is shown in Thirty six of 754 measurements showed supra-therapeutic tacrolimus levels (defined as >15 ng/ml). Frequencies of supra-therapeutic measurements were not different (P = 0.36) between EM (3/111), IM (28/575), or PM (5/68). Of the 36 supra-therapeutic levels, 27 fell into the first 4 days of treatment, and 10 of them occurred on the first day (-9) compared with IM (37%) or PM (9%). Moreover, the target C0 tacrolimus level of >6 ng/ml was achieved in EM patients not before day 12 of onset of therapy (Subtherapeutic tacrolimus levels (defined as <6 ng/ml) during the entire observation time were more common in EM patients  and 30 patients (25%), respectively. eGFR at discharge from the hospital was >60 ml/min in 27 patients. Most patients achieved an eGFR between >30 and ≤59 ml/min (n = 64 patients). Seventeen patients retained a severely decreased renal function (>15 and ≤30 ml/min), while 12 patients had an eGFR below <15 ml/min at discharge.No statistical significant effects of all tested genetic variants and related phenotypes  on AR, DGF, or renal function were found after correction for multiple comparisons . For the CYP3A4/5 combined genotypes, EM (n = 17) showed also a significantly higher dose requirement than both IM (n = 93) or PM (n = 11) at onset of therapy. The IM and PM groups did not show a significant difference in the daily doses, in contrast to CYP3A4*22. However, statistically significant differences between CYP3A4*1/*22 and CYP3A4*1/*22 were only observed at day 10 keeping in mind that the number of variant carriers for CYP3A4*22 is low in our study cohort. The CYP3A4/5 combined genotypes explain a greater part of variability in dose requirement (21.2%) compared with the isolated contribution of CYP3A4*22 (4.8%) corroborating previous data about the relevance of CYP3A5 for tacrolimus dosing.An important aspect to this study was to investigate the effect of the variants on the tacrolimus dose. To minimize rejection and toxicity after transplantation, the target tacrolimus Cndations . Already0 levels observed in patients treated with the same dose of tacrolimus can be explained in part by the genetic variation in CYP3A5. Yet, although CYP3A4*22 contributes to a lower rate to tacrolimus metabolism, CYP3A4*22 related higher C0 tacrolimus levels have been reported in some cohorts . This observation holds true for the entire observation period up to 16 days with a trend of significance after correction for multiple testing. Several studies reported a significantly reduced tacrolimus clearance (with a higher C0) in heterozygous patients for CYP3A4*1/*22 in the early period after renal transplantation (The exposure to tacrolimus (AUC of dose-adjusted levels) in our study was significantly higher (P = 0.016) in heterozygous antation . In contantation . One expCYP3A5*3/*3) showed significantly higher dose-adjusted tacrolimus AUC than expressers (CYP3A5*1/*3 or CYP3A5*1/*1). This resembles data from a meta-analysis by CYP3A4/5 combined genotypes, both the PM or IM cluster have significantly higher dose-adjusted tacrolimus AUCs in the first 16 days post-transplantation than EM. AUCs show a huge interindividual variability in IM and PM and do not differ significantly between these groups. Assessment of the CYP3A4/5 combined genotypes regarding AUC was not superior compared with the monogenic CYP3A5 analysis.Throughout the first 16 days post-transplantation, CYP3A5 non-expressers (0 > 15ng/ml) in heterozygous carriers of CYP3A4*22 (0 in the first week of transplantation. Most probably due to our lower dosing regimen (0.1 mg/kg body weight), supra-therapeutic tacrolimus levels were found only on 36 of 754 occasions, with a majority occurring in the first 4 days of tacrolimus therapy  may be a concern in CYP3A5 expressers or EM patients due to an enhanced metabolism toward inactive metabolites  on discharge, when controlling for confounders like HLA mismatch, % panel reactive antibodies, AB0 compatibility, valgancyclovir use, donor source, number of transplant, and type of induction therapy. CYP3A4*22 has been associated with DGF, but only with cyclosporine , which may explain why we did not observe significant effects of the tested genotypes on the clinical endpoints. We only performed genetic analysis using DNA from recipients but not from donors, which may explain missing genetic associations observed by others, e.g.,  and DGF . AlthougCYP3A variants explain interindividual variability of tacrolimus pharmacokinetics but do not impact on clinical outcome variables like AR, DLF, or eGFR. Notably, CYP3A4*22 isolated or in combination with CYP3A5 genotypes did not decisively improve the well-established value of CYP3A5 pharmacogenetic testing only to predict tacrolimus dosing. ABCB1 did neither significantly impact on tacrolimus pharmacokinetics nor on clinical outcome parameters.Our results confirm previous data indicating that The raw data supporting the conclusions of this manuscript will be made available by the authors, without undue reservation, to any qualified researcher.All subjects have given their written informed consent. The study was approved by the ethics committee of University Hospital, Tuebingen, Germany (616/2013BO2).EA-K was responsible for acquisition of all source data and contributed to the writing of the manuscript. SW performed or supervised statistical analyses and critically revised the manuscript. RT performed statistical analyses. ES was responsible for genotyping. CO recruited the patients and provided the clinical data. EW, MSc, and MSh were responsible for funding, conception of this study, interpretation of results, and critical revision of the manuscript. SJ performed statistical analysis and wrote the manuscript.This study was supported in part by the Robert Bosch Stiftung Stuttgart, Germany and in part by the Horizon 2020-PHC-2015 grant U-PGx 668353.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Elephas maximus indicus) in India between 2013 and 2017. Eight occurred amongst free-ranging wild herds, with three more in camp-raised orphans and two in captive-born calves. All were confirmed to have high levels of Elephant Endotheliotropic Herpesvirus type 1A (EEHV1A) DNA detected within gross pathological lesions from necropsy tissue by multi-locus PCR DNA sequencing. The strains involved were all significantly different from one another and from nine previously described cases from Southern India (which included one example of EEHV1B). Overall, eight selected dispersed PCR loci totaling up to 6.1-kb in size were analyzed for most of the 22 cases, with extensive subtype clustering data being obtained at four hypervariable gene loci. In addition to the previously identified U48(gH-TK) and U51(vGPCR1) gene loci, these included two newly identified E5(vGPCR5) and E54(vOX2-1) loci mapping far outside of the classic EEHV1A versus EEHV1B subtype chimeric domains and towards the novel end segments of the genome that had not been evaluated previously. The high levels of genetic divergence and mosaic scrambling observed between adjacent loci match closely to the overall range of divergence found within 45 analyzed North American and European cases, but include some common relatively unique polymorphic features and preferred subtypes that appear to distinguish most but not all Indian strains from both those in Thailand and those outside range countries. Furthermore, more than half of the Indian cases studied here involved calves living within wild herds, whereas nearly all other cases identified in Asia so far represent rescued camp orphans or captive-born calves.Thirteen new lethal cases of acute hemorrhagic disease (HD) with typical histopathogical features were identified in young Asian elephants ( The deaths of more than 100 young endangered Asian elephant calves worldwide with acute hemorrhagic disease (HD) have been documented to be associated with a novel type of herpesvirus called Elephant Endotheliotropic herpesvirus (EEHV) found at very high levels in blood or necropsy tissue samples. The first reported HD case occurred in a calf in a circus in Switzerland , 3. The Elephas maximus) born in captivity has been observed to have a fatality rate of about 80%. Overall, as reviewed by Long et al [Over the past 20 years, acute hemorrhagic disease occurring in young Asian elephants  have now all been completely sequenced directly from necropsy tissue samples –30. In cfamilies , 29–31. ene loci .Our earlier report involving DNA sequence data from several selected PCR gene loci from the first nine cases from India  revealedFig 1). The novel hypervariable E54(OX2-1) gene data from the unique segment shows no linkage at all to the standard EEHV1A versus EEHV1B chimerism patterns displayed by all six of the core gene loci examined previously [The present expanded genetic analyses reveal that there are many different ancient and highly diverged variants of EEHV1A associated with lethal HD disease in Southern India. Overall, proven or anecdotal cases are widespread in Asia and have now been reported in at least eight different range countries, indicating that EEHV HD represents a serious additional threat to the current and future reproductive success in zoos and the conservation of highly endangered free-ranging wild populations worldwide. In the new studies reported here, we have also examined a further 12 EEHV1-positive lethal cases associated with the two largest elephant sub-populations from the Western Gnats area of Southern India plus one case from Central India. In addition to the same six original PCR loci, two other variable PCR gene loci from the ends of the EEHV1 genome referred to as E54(vOX2-1) and E5(vGPCR5)  were inceviously , and is Table 1. They all displayed gross pathological features typical of those described previously [Twelve of the new cases of sudden HD deaths in young Asian elephants in Southern India were collected from a variety of locations across the Western Gnats area encompassing parts of Kerala State, whereas one came from Maharishtra State outside of this area. A list summarizing the major features and details available about each of the 13 new HD cases is provided in eviously , includiIn our previous studies worldwide, four separate PCR loci mapping across the central core segment of the EEHV1 genomes have been found to give consistent diagnostic distinctions between the two partially chimeric EEHV1A or EEHV1B genotypes, in which all examples within each of the two groups show common patterns of approximately 3.5% nucleotide polymorphisms relative to one another . TherefoTo unambiguously demonstrate that individual EEHV1 samples represent distinct and epidemiologically independent strains, it is necessary to evaluate several additional PCR loci representing more variable genes , 20, 32.In contrast, the new E5(vGPCR5) and E54(vOX2-1) loci mapping towards the ends of the genome outside of the conserved core segment both fail to either identify or link to the characteristic classic chimeric core EEHV1A versus EEHV1B subtype patterns. Instead, the E5(vGPCR5) locus falls into three distinct subtype groups referred to as A, B and C where the divergence is largely confined to a 200-bp central block with more than 25% polymorphic nucleotide positions (including a five aa deletion in the A strains). These three E5(vGPCR5) subtype clusters do not show linkage to the subtype patterns found at any other loci examined. Furthermore, the E54(vOX2-1) locus displays up to 15% nucleotide and aa divergence levels that distinguish amongst most but not all independent EEHV1 strains (including the otherwise largely invariant chimeric EEHV1Bs). However, the E54(vOX2-1) patterns obtained are too complex to easily categorize into recognizable subtype clusters. Nearly complete data are included for all four hypervariable loci from each of the 13 new cases and we have also added results for the E5(vGPCR5) and E54(vOX2-1) loci as well for many of the previous older India cases. Overall, complete data at all eight PCR loci tested were obtained for nine of the new cases, with just one locus missing for IP152 and IP213, whereas only three loci were successfully amplified and sequenced for case IP169 (which was derived from a heavily putrefied tissue sample).Table 2. A summary of the subtyping data results obtained for all 22 Indian cases examined is presented in Table 3, although only a plus or minus result is recorded for the E54(vOX201) locus. These data include newly added or revised subtype designations for the old India cases within the U71-gM, U77(HEL) and U60(TERex3) loci.All good quality data from the resulting PCR DNA sequence analyses at up to eight non-adjacent PCR loci for each of the new Indian samples  plus selected additional loci for several of the old India samples has been assembled, edited and annotated then deposited in GenBank in a total of 110 new files plus five expanded files, whose GenBank accession numbers are listed together with sizes and map coordinates of all eight PCR loci in Fig 2 and for the other seven PCR loci in  These diagrams show the relative positions of all nucleotide polymorphisms across each locus for our entire set of Asian case samples, together with available data for the five Myanmar and Sumatra cases that will be described elsewhere . For comparison, data for the equivalent regions of the intact prototype EEHV1A(Kimba) and EEHV1B(Emelia) genomes (GenBank Acc Nos. KC618257 and KC462164) is included for all loci. The charts also contain matching data for between seven and 12 other selected EEHV1 examples, encompassing all known subtypes, from amongst either European (EP#) or North American (NAP#) samples.DNA level difference data for the U48(gH)-TK PCR locus are presented in a graphic chart format in Fig 3 and for each of the other seven PCR loci in . With the single exception of the E5(vGPCR5) locus, corresponding regions from one or more of either the prototype EEHV2, EEHV5 or EEHV6(NAP35) genomes were available to be used as comparative or outgroup data for both the charts and phylogenetic trees. Finally, similar protein level phylogenetic trees illustrating the results for U48(gH) are presented in Fig 4 together with the results for the other three most hypervariable loci U51(vGPCR1), E5(vGPCR5) and E54(vOX2-1) in  Note that only data for the gH coding region (not the adjacent and overlapping TK coding segment) is included from the U48(gH)-TK PCR locus here. Nevertheless, the DNA and protein level trees for this locus are virtually identical with the distinction between the A1 and A2 subtypes within Table 4 also presents direct nucleotide number differences at each locus compared to the prototype EEHV1A(Kimba) and EEHV1B(Emelia) strains, which total 369 and 95-bp respectively.DNA level phylogenetic trees using the same DNA sequence data for the U48(gH)-TK PCR locus are presented in Overall, the results obtained for the new Indian samples revealed a set of 13 novel and easily distinguishable EEHV1A strains that display similar overall levels of variability to those observed across these same loci amongst all other North American, European and Asian cases that we have examined previously. Although just a few loci from several of the new strains did prove to be identical across two or more samples, none were identical across all loci. Many subtle differences from most or all previous samples evaluated were evident, but there were no new subtypes or otherwise strikingly novel patterns revealed. The pair of cases reported previously to occur three days apart at the same Indian orphan camp in calves that had been born and orphaned in two different locations within the Western Knats (IP06 Nirangen and IP07 Aswathi) remains the only pair of completely identical samples seen so far in India . However show the patterns of nucleotide variation found across the standard conserved U38(POL), U60(TERex3), U71-gM, and U77(HEL) PCR loci from all Indian cases compared to representative and prototype examples from our earlier studies amongst North American and European cases, as well as five more from other Asian range countries. The variations here that were found to be common to all examples of the classic B-subtype chimeras (denoted by solid circles) at each of these four loci compared to the remaining far more numerous non-B-subtype versions all fall into the range of 3 to 5% differences at the nucleotide level. Whilst many epidemiologically unrelated strains display identical sequence patterns to one another at certain single individual loci this never continues across multiple loci. Nevertheless, there is also a sufficient level of sporadic polymorphisms even amongst members of the same subtype clusters, such that most strains can be distinguished from one another at many or all loci. The two exceptions to this rule among Asian samples as mentioned above (IP06 and IP07) plus SP01 and SP02) now bring the overall total to six known pairs of epidemiologically connected cases of HD that occurred at the same facility at close to the same time and are identical to one another at all loci tested.The first four difference charts presented in Except in U38(POL), the non-B strains generally split into one or more additional consistent slightly diverged patterns that we usually designate as either A or C-subtypes  and that can sometimes be differentiated further as A1, A2, A3 etc. or as A/B or C/D if apparently recombinant. For example, at the U71-gM locus, where the A and B subtypes display 32 common polymorphisms, we also define a third C-subtype group, which consists of just two North American examples (NAP11 = Kumari and NAP17 = Singgah) that are clearly intermediates between the A and B cluster patterns with either 20 or 25-bp differences from both. In another (but rare) example, just a single consistent nucleotide difference T450G occurring in over one third of the strains was considered sufficient to define a C- versus A-subtype for the U77(HEL) locus, despite there also being several other more randomized single polymorphisms present. That same position has a T450A polymorphism in the B- and D-subtypes.Table 3), but has not been seen elsewhere. Similarly, for U60(TERex3), the situation is slightly more complex in that there are again 13 subtype-B defining polymorphisms common to IP93 and all but one of the classic B-subtype chimeras. Finally, the U77(HEL) locus gives a consistent pattern of 19 common polymorphisms across all but one of the classic subtype-B examples shown, including IP93, with a total of 18 additional strain-specific mutations amongst the non-B subtypes set. The single exception is NAP19 (= Haji) which instead contains an additional recombinant chimeric A-subtype segment across three adjacent loci, including U60(TERex3), U71/gM and U77(HEL), but remains a classic B-subtype on both the left and right sides of that region [The simplest pattern occurs at the U38(POL) locus, where amongst the Indian and several selected prototype examples the predominant feature is just the subtype-A versus subtype-B diaspora, with 14 common nucleotide polymorphisms between them, plus a total of ten additional rare single point mutations. One of the latter, a T to C at position 960 occurs in nine of the India samples  locus is presented directly in the text as At the U48(gH-TK) DNA locus, the new India samples included 2x C1, 2x D, 2x E and 5x F subtypes compared to 1x A2, 1x C1, 2x C3, 2x D, 1x E, 1x F and 1x B for the old India set. At this locus as well, the three Indian Es were identical, and again as shown in Figs Figs 3). Even the only two known examples of EEHV6 (both included in the charts) show a similar level of nearly 30% divergence from each other and all EEHV1s across the LHS U48(gH) segment, whereas they are nevertheless largely invariant across the RHS U48.5(TK) segment, whilst still maintaining even higher levels of divergence from both the EEHV1Bs and also from the entire remaining EEHV1 A to F subtypes group. Note that the protein phylogenetic tree derived from this locus in Fig 4 encompasses only the highly variable U48(gH) coding segment not the less variable U48.5 TK segment.Interestingly, the U48(gH)-TK locus displays a dramatic internal dichotomy with the level of nucleotide divergence between all six subtypes across the first half (i.e. at positions 1 to 455 within the bulk of the U48(gH) gene segment that does not overlap with the TK gene) being much higher than across the second half encompassing the U48.5(TK) gene segment. In fact, the overall level of nucleotide polymorphism (omitting deletions) across the U48(gH) gene portion on the LHS of this locus amongst all the EEHV1 strains shown in the chart is as high as 37%, but drops to 26.6% when the B-subtype examples are omitted. In comparison, the value is 24.3% across the TK gene coding block on the RHS, but falls dramatically to only 4.5% when the B-subtypes are omitted. Across this whole locus, the six known B-subtypes are almost completely identical amongst themselves, but differ hugely from all the other EEHV1s by around 35% overall at the nucleotide level , the new India cases included the following subtypes, 2x A2, 1x D1, 5x E and 3x E/A, whereas the old India set included 2x A2, 1x D1, 1x D2/A, 3x E, 1x E/A and 1x B. Neither group contained any A1 or C subtypes and only the original set included a single B subtype (IP93). All seven E subtype examples were identical to one another at the nucleotide level as also were the four E/As and the two D1s, but there were three polymorphic positions amongst the four A2s. Most of them also showed identity to one or more from a subset of the North American cases as well. At the protein level, even the E plus E/A subtypes proved to be identical with no polymorphisms at all across all 11 Indian examples . No data was available at this locus for case IP213. Amongst the Indian samples shown on the chart (including the single B-subtype IP93) there are a total of 61 out of 670 polymorphic nucleotide positions overall, (excluding deletions), representing 9.1% divergence, but at this locus the major subtype-defining variations are largely confined to the five clustered patterns of aa insertions and deletions within the “hot-spot” between nucleotide positions 512 and 570. Once again, all six classic B-subtypes (including NAP19 and IP93) are both very distinctive and identical here across nucleotide positions 450 to 600, although NAP33 and NAP45TW do differ significantly from the others within the first 300-bp of this locus.For the U51(vGPCR1) DNA locus (S13 and ), where the previously analyzed North American and European cases fall into just three roughly equally abundant subtypes , the new India cases yielded 1x A, 4x B and 6x C with three of the latter  being identical C2’variants, whereas all five old Indian cases analyzed (including IP93) were B-subtypes at this locus. No data is available here for the other four old India cases IP01, IP05, IP60 or IP91. Once again, this locus shows a curious dichotomy whereby most of the subtype-specific nucleotide and nearly all of the protein variability occurs just within the RHS C-terminal segment of the protein from position 485 to 710. Despite significant (but not subtype-defining) nucleotide variation  within the LHS segment  there is very little aa variation here . However, the overall nucleotide polymorphism level reaches 21% between positions 485 to 965 and rises further up to 31% just between positions 485 and 710. The overall nucleotide divergence common to most examples of the A, B and C subtypes from the consensus here measures out at just about 4%, 2% and 3% respectively across the whole protein and is again heavily concentrated just between positions 485 to 710 . Only a small fraction of strains within a single subtype display identity here, but they do still each closely resemble one of the appropriate selected prototypes given from amongst the North American cases. Whilst four of the six classic B-prototypes shown  do happen to fall into the E5(vGPCR5) B-subgroup here, there are six other classical non-B chimera examples from India that also fit into the same B-subtype group here, clearly showing that there is either no linkage or at most just a highly scrambled residual level of linkage to the classical EEHV1A versus EEHV1B chimerism patterns in E5(vGPCR5).For the E5(vGPCR5) locus   that data covers a segment that is too small to allow meaningful phylogenetic comparisons in the matching DNA and protein trees (S14 and ). Therefore, data for EEHV5 (Vijay) is used instead as the outgroup for E54(vOX2-1) in S14 and . Remarkably, although the 290-aa double immunoglobulin-like domains of this viral version of this captured host cell protein remain highly conserved at the aa level , it is still highly variable at the DNA level, exhibiting up to 35% overall polymorphic nucleotide positions occurring amongst the 29 independent EEHV1 case samples illustrated in the DNA polymorphisms chart in S7 Fig and DNA tree in S14 Fig.Finally, for the E54(vOX2-1) locus, data was obtained for all 13 new India cases and four of the old India cases as shown in S7 Fig) across almost the whole length of the vOX2-1 gene, but switches to being identical to both IP212 and NAP45TW over the final 200-bp. As an example of one of the highest levels of diversity seen across the E54(vOX2-1) locus amongst EEHV1 strains, IP06 and IP11 differ here by 136 out of 850-bp (15%) at the nucleotide level.Despite showing clear evidence that the E54(vOX2-1) locus does display extensive but complex subtyping effects, with short patches of matching nucleotide similarity occurring between some strains, the resulting patterns are far too scrambled (presumably by homologous recombination) to be able to cleanly define any specific subtype clustering. Nevertheless, there are multiple examples where segments of several different strains display obvious high levels of partial resemblance or identity, as well as several segments where the divergence reaches similar high levels to that between EEHV1A and EEHV2. The most notable of these “hot-spots” are from nucleotide positions 10 to 160 in NAP45TW, 600 to 680 in NAP14, 500 to 600 in IP143, 500 to 650 in IP164, IP165 and IP213 plus 590 to 660 in IP212. Interestingly, one of the Indian strains IP11 shows nearly the same level of divergence from all other EEHV1 strains as for EEHV5 and EEHV6  and protein tree , proved for the most part to be highly diverged from one another, whilst also showing no significantly greater than usual differences from any of the non-B subtype examples.When just IP11, IP212 and NAP45TW are omitted from the analysis, the total level of polymorphisms across the E54(vOX2-1) genes in EEHV1 strains drops from 285 out of 806 bp (35%) to 199 out of 806 bp (25%). Furthermore, the high preference for displaying synonymous rather than non-synonymous aa changes here is so extreme that across one 114-bp section from positions 489 to 603 there are a total of 31 out of 34 successive codons (excluding gaps) that have polymorphism at the wobble position with only seven other non-wobble positions having polymorphisms within the same region. Unexpectedly, like E5(vGPCR5) above, this locus from close to one end of the novel segment of the genome does not show any obvious linkage to the conserved core region EEHV1A versus EEHV1B chimerism patterns. In fact, the vOX2-1 sequences from all six representative examples of classic core B-subtype genomes NAP14, NAP19, EP18, NAP33, NAP45TW, NAP49 and IP93 (as denoted by solid circles) that are included in the DNA difference chart (Table 2), several additional common trends have indeed emerged. Firstly, amongst the four conserved region loci, the unique non-syngeneic T to C polymorphism in U38(POL) has now been found in nine of the 20 South India EEHV1 examples studied, but so far in just one other (NAP31) from a total of 45 other EEHV1 examples that we have evaluated from outside of India, and not in Thailand either. Somewhat similarly, although the difference between the assigned A and C subtypes in U77(HEL) are based solely on a single T450G polymorphism in the latter, 17 of the 20 cases from India fall into the C group  with 3x C and 2x A from other parts of Asia, whereas amongst the combined European and North American sets there were instead 13x A, 5x B, 15x C and 2x D and in Thailand there were 3x A, 2x B, 7x C and 3x D.Zachariah et al  pointed Fig 5.Secondly, no fewer than 12 out of the 20 different South Indian EEHV1A strains evaluated at the U51(vGPCR1) locus (60%) have proven to be either E or E/A-subtypes, whereas only four out of 34 (12%) from European and North American EEHV1A examples were of these subtypes (plus one from Myanmar). In contrast, 11 out of the 13 EEHV1A cases from Thailand examined at this locus  were insFig 6.Thirdly, amongst the Indian EEHV1A cases, four examples of the U48(gH) locus were C-subtypes, plus 4x D, 3x E, 5x F but just 1x A and 1x B, with all three from Myanmar being D-subtypes. This compares to 14x A, 6x C, 4x D, 3x E, 2x F and 5x B-subtypes here from a total of 34 European and North American cases, but there is no data available for the U48(gH) locus nor for E5(vGPCR5) or E54(vOX2-1) from Thailand. Again, the difference in subtype distribution patterns between the India cases and the examples evaluated by our group from both North American and European examples is illustrated graphically in Fig 7, in contrast to the E5(vGPCR5) subtype distribution patterns found in North America and Europe, the 21 India and Myanmar cases evaluated here included instead 11 B-subtypes and nine C-subtypes, with just one A-subtype being detected (IP208). Again, several examples of non-epidemiologically related localized identity occurred amongst the India cases, with the most notable being the three identical cases of C2’ strains here. Amongst the six non-Asian chimeric EEHV1B strains, four were B-subtypes at this locus, with one each being A and C subtypes and the single Indian IP93 EEHV1B strain was also a B-subtype here. However, nine other examples of B-subtypes in E5(vGPCR5) were from strains that have classic EEHV1A chimeric patterns.Fourthly, for the E5(vGPCR5) locus, our studies with European and North American cases revealed that they split up into three distinct subtype clusters, with a total of 12 being defined arbitrarily as A-subtypes (including the Kimba and Raman prototypes), 14 being B-subtypes and six being C-subtypes, including the classic chimeric EEHV1B prototype strain EP18 = Emelia). As shown in Finally, returning to the U54(vOX2-1) locus, it was quite remarkable to find that several otherwise unrelated Indian genomes exactly matched to one of the Asian or even North American genomes at this locus only. As expected, the six known epidemiologically related identical pairs occurring at nearly the same time at the same facility, including IP06 plus IP07 from India, SP01 plus SP02 from Sumatra, EP20 plus EP21 from the United Kingdom and EP24 plus EP25 from Germany, as well as both of the surviving NAP33 plus NAP34 and NAP39 plus NAP40 case pairs in the USA were indeed identical at all loci tested. But surprisingly, five pairs of non-epidemiologically related Asian samples, namely IP06/IP07 plus IP240, IP165 plus IP239, IP200 plus IP208 and IP143 plus MP01, as well as IP93 plus MP03 proved to be identical here also. In addition, two different Indian samples IP152 and IP213 formed identical pairs here with recent even more obviously unconnected USA samples NAP80 and NAP63 respectively. However, for all five of these latter groups of matching pairs within the U54(vOX2-1) locus, the identity occurred only at this one locus and their genomes differed extensively elsewhere. Similar situations of localized identity amongst E54(vOX2-1) loci only have also been observed amongst seven of the 34 apparently epidemiologically unrelated cases examined previously from North America namely the NAP30 plus NAP73 pair, as well as the NAP17 plus NAP80 pair, and also for three other identical examples found in cases NAP29, NAP45TW plus NAP75.Whilst the four conserved PCR loci do also all exhibit many examples of localized identity at single PCR loci among unrelated sample pairs, the phenomenon was more unexpected and seemingly more dramatic within the hypervariable loci and especially so for E54(vOX2-1). However, the other three hypervariable loci do also show many examples of the same effect (even just amongst Asian samples). For example, in U51(vGPCR1), all eight Asian subtype-Es were identical to one another at the nucleotide level (and just one bp different from the USA prototype NAP13). Similarly, three unrelated Indian subtype-E/As  were identical, as also were two Indian subtype-Ds (IP43 plus IP183) and two Indian subtype A2s (IP91 plus IP239). For the E5(vGPCR5) locus, the same applies to IP165, IP239 plus IP240 (subtype-C) as well as four other pairs including IP143 plus IP222 (subtype-C), IP93 plus IP152 (subtype-B), IP143 plus IP222 (subtype-C), IP169 plus IP213 (subtype-B) and MP01 plus MP02 (subtype-B). Finally, at the U48(gH-TK) locus all six Asian subtype-Fs  were identical to one another (as well as to the North American prototype NAP17), and IP43, IP183 plus IP239 (subtype-C), as well as IP11, IP164 plus IP165 (subtype-E), IP60 plus IP208 (subtype-D) and again MP01 plus MP02 (subtype-D) also all exhibited identity here.Although the intact DNA genomes of two EEHV1A prototype strains and one EEHV1B prototype strain  have been determined and annotated , 26, 30,Elephas maximus host populations in Western zoos obviously had recent origins as imports from multiple different Asian countries. Clearly, the introduced Asian virus strains endemic to individual source countries and herds would be expected to have both prior localized ancestral divergence associated with evolutionary drift amongst themselves, coupled with some degree of additional opportunities for genetic mixing and subsequent recombination exchanges between viruses from different Asian elephant host populations as well. But evidently the levels of subtype divergence and the patterns of localized preferential subtype enrichment are both very large and unexpectedly complex.Overall, as described in detail in the results section, the data obtained here for the 22 Indian cases display essentially the same wide range of subtype variability as found across all cases examined previously from Europe and North America. However, for the first time some degree of differentiation in the relative frequency of subtype patterns observed between both the Indian set and the Thailand set of strains and between both Asian range country sets versus European and North American subtype patterns can be discerned. These preferential subtype pattern trends apply only at the individual PCR loci level and do not show any evidence of consistent genome-wide effects or even partial linkage across adjacent loci. That the overall subtype patterns found in Asia and Europe-North America are similar is hardly surprising considering that the extant −8 changes per nucleotide per year [5 bp in size encoding around 100 proteins this is equivalent to about one nucleotide (and amino acid) change per average-sized gene every 100,000 years and in the vicinity of 10% overall nucleotide divergence every 10 million years. These values mostly apply only to well-conserved common core genes, with many of the hypervariable genes, which often fall into multiple distinct clustered subtype lineages, apparently representing very anciently diverged versions that in some cases may even have arisen originally from rare exchange events with other closely related virus species. Evidently, large segments of both the novel and conserved segments of the different subtypes later become unlinked and scrambled after presumably rather extensive genetic exchanges between strains by homologous recombination. Even although the extant modern EEHV1 virus population as a whole clearly represents a single recombining species, the last common ancestor ages (LCA) for different segments and hypervariable genes of different individual strains consists of a complex mixture of pieces derived from multiple diverged genome types and with wide ranges of both modern and anciently acquired variations. Some of the gene subtypes observed here may have diverged by standard genetic drift mechanisms beginning tens of millions of years ago then been reassembled into complex chimeric forms by relatively rare interspecies level recombination events. Therefore, the overall EEHV1 population may be best described as consisting of a swarm or quasi-species, although (unlike HIV for example) this extremely high level of variation would not be expected to change at all within the lifetime of a single individual host animal.Unlike HIV and many RNA viruses, herpesvirus genomes generally have relatively low rates of genetic drift that have been estimated at 3 x 10per year . For genCurrent biogeographic barriers are believed to have resulted in four major distinctive populations of Asian elephants in India located in Northern, Northeastern, Central and Southern areas, with the Southern India group being further divided into two sub-populations occupying either side of the Palaghat gap. Data from both mitochondrial DNA genome analysis and nuclear satellite marker sampling suggest that the elephant populations on either side of the Palaghat gap have been effectively separated for 120,000 years , 36. AllBecause most HD cases are believed to be primary infections, we expect that where they died is more relevant here than where they were born. Possible correlations include seven out of eight of the POL T960C polymorphisms being from the NBR area, as well as eight out of eight of the U51(vGPCR1) subtype Es being from the A/P area, whereas three out of the four U51(vGPCR1) E/As subtypes came from the NBR area. Similarly, five out of six of the U48(gH-TK) examples came from the A/P area , whereas three out of three U48(gH-TK) subtype Es came from the NBR area. However, most other subtype-specific features appear to have scrambled or mixed up locations. Therefore, overall, we have not been able to discern any clear patterns of preferential localization of more closely related EEHV1 strains to either side of the Palaghat gap, indicating that (perhaps with just a few exceptions) these numerous anciently-derived chimeric patterns were most likely largely randomized prior to formation of that new biogeographical barrier and that the 120,000 years separation probably represents too short a time period for distinctive differences or linkage patterns at most locations within the viral genomes to have emerged or to become recognizable.EEHV-associated HD remains a serious problem in Asian elephant populations worldwide . With reThese procedures were carried out as described previously , 14, 20.These procedures followed those described in Zachariah et al , except U38(POL) Locus: Core segment, shows low level classic chimeric A versus B subtypes.5’-GTA TTT GAT TTY GCN AGY YTG TAY CC-3’R1 LGH6711 5’-TGY AAY GCC GTN TAY GGA TTY ACGG-3’R2 LGH6712 5’-ACA AAC ACG CTG TCR GTR TCY CCR TA-3’L1 LGH6710 Round 1 R1/L1 = 530-bp, round 2 R2/L1 250-bp.U60(TERex3) Locus: Core segment, shows low level classic chimeric A versus B subtypes.5’-GTT TGT AGT AAA TGC CGG ATC-3’R1 LGH6671 5’-GTC GGC TAA ATG TTC TTG -3’R2 LGH2429 5’-GTA CGT CCT TTC TAG GCT CAC-3’L2 LGH2430 5’-CAT GTT GTG CAG GCA CTC TTC-3’L1 LGH6672 Extended version round 1 R1/L2 = 780-bp; Short version R2/L2 = 340-bp,U71-gM Locus: Core segment, shows low level classic chimeric A versus B subtypes.5’-CTA TGG GAT CCG AAC TTT C-3’R1 LGH6749 5’-CTT TCT AAG GGG GTT TGT TGC-3’R2 LGH6750 5’-CTA CAT GCC CAT GCA GAT AGG-3’L2 LGH6752 5’-GAA GTC CTG CTA GCC CCY TAC-3’L1 LGH6751 Round 1 R1/L1 = 750-bp, second round 2A R2/L1 = 730-bp, second round 2B R1/L2 = 730- bp, third round 3AB R2/L2 = 710-bp.U77(HEL) Locus: Core segment, shows low level classic chimeric A versus B-subtypes.5’-CCA GTC AAC GTA TAG CTC GTA G-3’R1 LGH6649 5’-GCA AGG TRG AAC GTA TCG TCG-3’R2 LGH6743 5’-CTG CGT GTA ACA TGT TGG C-3’L2 LGH7885 5’-CAC AG(A/C) GCG TTG TAG AAC C-3’ (= LGH6742)L1 LGH3198 Round 1 R1/L1 = 980-bp, round 2A R1/L2 = 950-bp, round 2B R2/L2 = 680-bp.U51(vGPCR1) Locus: Six major subtypes including distinctive classic chimeric B-subtypes.5’-GAT TGT GAA CGC TGT ATG CT-3’R1 LGH7506 5’-(GAC) AGG TGG TAC TGT ATG ATG TGC-3”R2 LGH7470B 5’-CGT GAT ACG CTT CAA AAC ATA CA-3’L2 LGH5200A 5’-GAC TTT CTT CGT AGC CCT CGT CTT-3’L1 LGH4963B Round 1 = R1/L1 = 910-bp; round 2A R1/L2 = 750-bp; round 2B R2/L1 = 730-bp, third round 3AB = 570-bp.U48(gH)-TK Locus: Six major subtypes including distinctive classic chimeric B-subtypes. Maps within CD-II core chimeric domain5’-CT(A/G) CAT T(T/G)(A/C) CCA AAG TAT GGA AGT A-3’R1 LGH7981 5’-CRT YTA TAT CAT CAA ARA CYT CAC A-3’R2 LGH7982 5’-CAG CCT TCA AGC GGC ATA CAC TG-3’L2 LGH7984 5’-GGT AGG TTC ACC TAC ATG GAA CTT C-3’L1 LGH7985 Round 1 R1/R2 = 1080-bp. Round 2A R1/L2 = 920-bp, 2B R2/L1 = 1040-bp, third round 3AB R2/L2 = 860-bp.E5(vGPCR5) Locus: Three subtypes only, unrelated to classic chimeric A plus B subtypes.5'-CCG TTT ACT TGC GTA GTA GGT ACG-3' (1)R1 LGH8507 5'-CCG ATC TAT GTA CTT ACG YTA GCG GTG-3’ (70)R2 LGH8552 5'-CAC GTC CGT ATG TGA CAG GTA CAA TC-3' (920)L2 LGH8558 5'- GAC GTG TTT CCT AGG ATT GTC AAA G-3' (1000)L1 LGH8508B First round R1/L1 = 1000-bp, round 2A R1/L2 = 980-bp, round 2B R2/L1 = 930-bp.U54(vOX2-1) Locus: Patterns are too complex to assign subtype clusters. No correlation with classic chimeric A plus B subtypes.5’-ATG CTT CAG AGA AAG TA AGG TAC-3’R1 LGH8471 5’-GGT CGT AAC GCA AGA TGA GCG AG-3’R2 LGH9132 5’-GAT GCC TTC TAC GCC ACT TGT AAC AG-3’L2 LGH8506 5’-GTG TTG CCG CCA CGA TGC TTC TAC G-3’L1 LGH8472 Round 1A R1/L1 = 910-bp; round 1B R1/L2 = 890-bp; round 2A R2/L1 = 740-bp; round 2B R2/L2 = 720-bpS1 FigFig 2 except for also including data for the two Sumatran cases (SP#) and the use of both the prototype EEHV2(NAP12) and EEHV6(NAP35) genome data for comparison.As for (TIF)Click here for additional data file.S2 FigFig 2 except for also including data for the two Sumatran cases (SP#) and the use of both the prototype EEHV2(NAP12) and EEHV6(NAP35) genome data for comparison.As for (TIF)Click here for additional data file.S3 FigFig 2 except for also including data for the two Sumatran cases (SP#) and the use of both the prototype EEHV2(NAP12) and EEHV6(NAP35) genome data for comparison.As for (TIF)Click here for additional data file.S4 FigFig 2 except for also including data for the two Sumatran cases (SP#) and the use of the EEHV6(NAP35) genome data rather than EEHV2(NAP12) for comparison.As for (TIF)Click here for additional data file.S5 FigFig 2 except for also including data for the two Sumatran cases (SP#) and the use of the prototype EEHV6(NAP35) genome data rather than EEHV2(NAP2) for comparison.As for (TIF)Click here for additional data file.S6 FigFig 2 except that no equivalent data is available for comparison from either EEHV2 or EEHV6.As for (TIF)Click here for additional data file.S7 FigFig 2 except for also including partial data for EEHV6(NAP42D) and intact matching data for the EEHV5A(EP24 = Vijay) genome for comparison.As for (TIF)Click here for additional data file.S8 FigFig 1) are marked with solid circle motifs.Bayesian linear phylogenetic tree generated in MEGA5 by the maximum likelihood method from the same aligned nucleotide data set as in (TIF)Click here for additional data file.S9 FigFig 1) are marked with solid circle motifs. Note that NAP19 is an unusual hybrid EEHV1B genome with an internal recombinant 24-kb EEHV1A segment cross the U60(TERex3) locus.Bayesian linear phylogenetic tree generated in MEGA5 by the maximum likelihood method from the same aligned nucleotide data set as in (TIFF)Click here for additional data file.S10 FigFig 1) are marked with solid circle motifs. Note that NAP19 is an unusual hybrid EEHV1B genome with an internal recombinant 24-kb EEHV1A segment cross the U71-gM locus.Bayesian linear phylogenetic tree generated in MEGA5 by the maximum likelihood method from the same aligned nucleotide data set as in (TIF)Click here for additional data file.S11 FigFig 1) are marked with solid circle motifs. Note that NAP19 is an unusual hybrid EEHV1B genome with an internal recombinant 24-kb EEHV1A segment cross the U77(HEL) locus.Bayesian linear phylogenetic tree generated in MEGA5 by the maximum likelihood method from the same aligned nucleotide data set as in (TIF)Click here for additional data file.S12 FigFig 1) are marked with solid circle motifs.Bayesian linear phylogenetic tree generated in MEGA5 by the maximum likelihood method from the same aligned nucleotide data set as in (TIF)Click here for additional data file.S13 FigFig 1) are marked with solid circle motifs.Bayesian linear phylogenetic tree generated in MEGA5 by the maximum likelihood method from the same aligned nucleotide data set as in (TIFF)Click here for additional data file.S14 FigFig 1) are marked with solid circle motifs.Bayesian linear phylogenetic tree generated in MEGA5 by the maximum likelihood method from the same aligned nucleotide data set as in (TIFF)Click here for additional data file.S15 FigFig 1) are marked with solid circle motifs.Bayesian linear phylogenetic tree generated from translated amino acid data in MEGA5 by the maximum likelihood method from the matching aligned dataset as in the (TIF)Click here for additional data file.S16 FigFig 1) are marked with solid circle motifs.Bayesian linear phylogenetic tree generated from translated amino acid data in MEGA5 by the maximum likelihood method from the matching aligned dataset as in the (TIFF)Click here for additional data file.S17 FigFig 1) are marked with solid circle motifs.Bayesian linear phylogenetic tree generated from translated amino acid data in MEGA5 by the maximum likelihood method from the matching dataset as in the (TIFF)Click here for additional data file.