The TBSV viral RNA gets recruited to the membrane from the soluble fraction with the help of TBSV replication proteins and host factors present in the yeast CFE. The in vitro RNA recruitment reaction was performed according to [31] , except that 32 P-labeled DI-72 (+)repRNA were used and rCTP, rUTP, 32 P-labeled UTP, and Actinomycin D were omitted from the reaction. As a negative control, a recruitment-deficient repRNA, termed C 99 -G mutant, was used (Fig. 4F , lane 2) [23] . This mutant RNA is not recognized by p33/p92 replication proteins and it does not replicate in plants, in yeast or in the CFE in vitro [23, 31, 52, 77] . The RNA recruitment assay results in the assembly of the functional viral replicase, when wt repRNA is used, and nonfunctional replicase when the C 99 -G mutant is used in the assay (J. Pogany and P.D. Nagy, not shown) [31] . Inhibitors DB and GM were added at final concentration of 150 and 100 mM, respectively. After two hours of incubation at room temperature, 1 ml of reaction buffer was added to the in vitro assay, followed by incubation on ice for 10 min. Samples were centrifuged at 35,0006 g for 1h, and the pellet was washed with 1 ml reaction buffer, followed by centrifugation at 35,0006 g for 10 min. The membrane-bound repRNA was extracted from the pellet by adding 0.1 ml stop buffer and 0.1 ml phenol/chloroform and vortexing, followed by isopropanol/ammonium acetate precipitation [52] . The RNA samples were analyzed by denaturing PAGE and phophoimaging as described [52] . Figure S1 Schematic presentation of the random mutagenesis strategy used to obtain 6,000 eEF1A mutants. (A) The yeast strain (tef1Dtef2D carried a plasmid that expressed one of the random eEF1A (TEF1) mutants from the native promoter. Each yeast strain also carried pESCHIS4-ADH-His33/CUP1-DI-72 and pRS317-Tet-His92 to induce TBSV repRNA replication as described in the M&M section. (B) Additional experiments on the effect of eEF1A mutations on TBSV repRNA accumulation in yeast. The yeast strain expressed only one form of eEF1A, as indicated. Top panel: Replication of the TBSV repRNA was measured by Northern blotting 24 h after initiation of TBSV replication. (C) The accumulation level of repRNA was normalized based on the rRNA (the 18S ribosomal RNA levels were estimated by Northern blotting). Panels (D), (E) and (F) show the accumulation of p92 pol , p33 and eEF1A, respectively, estimated by Western blotting using anti-His and anti-eEF1A antibody. (G) SDS-PAGE analysis of total protein extract from the above yeast strains, after Coomassie blue-staining. Found at: doi:10.1371/journal.ppat.1001175.s001 (0.15 MB PDF) Figure S2 Binding of eEF1A to TBSV and TCV replication proteins in vitro. (A) MBP-tagged TCV p88C (lacking the p28overlapping domain from the N-terminus), MBP-TBSV p92, MBP-TBSV p92C (lacking the p33-overlapping domain from the N-terminus) and MBP-TBSV p33 or MBP (1 mg each) were separately immobilized on amylose beads, followed by incubation with a cytosolic extract prepared from yeast. The bound host proteins were eluted from the beads and were analyzed by 10% SDS-PAGE and detected via Western blotting using anti-eEF1A antibody (Top panel). The affinity-purified recombinant MBP-TCV p88C, MBP-TBSV p92, MBP-TBSV p92C, MBP-TBSV p33 and MBP were analyzed by 10% SDS-PAGE and Coomassie blue-staining (Bottom panel). (B) The effect of eEF1A mutations on binding to the viral p33 and p92 proteins in vitro. MBP-tagged p92, p33 or MBP were separately immobilized on amylose beads, followed by incubation with a cytosolic extract prepared from yeast expressing wt or mutated eEF1A. The bound eEF1A was eluted from the beads and were analyzed by 10% SDS-PAGE and detected via Western blotting using anti-eEF1A antibody (Top panel). The affinity-purified recombinant MBP-TBSV p92, MBP-TBSV p33 and MBP were analyzed by 10% SDS-PAGE and Coomassie blue-staining (Bottom panel). (C) The effect of eEF1A mutations on binding to the viral repRNA. CFE containing WT or mutated eEF1A was incubated with biotin-labeled DI-72(+) repRNA. Then the repRNA was captured with streptavidincoated magnetic beads, followed by elution of the co-purified proteins from the beads. Western blot analysis shows the amount of co-purified eEF1A using anti-eEF1A antibody. Found at: doi:10.1371/journal.ppat.1001175.s002 (0.12 MB PDF) Figure S3 Lack of inhibition of TBSV repRNA replication by Cyclohexamide in a cell-free TBSV replicase assay. The cell-free TBSV replicase assay was performed as described in Fig. 4 . Cyclohexamide was added in the following amounts: 0, 2, 10, 50, 100 mg/ml. The membrane-bound tombusvirus replicase in a yeast lysate was solubilized with Triton X-100/SB3-10 detergent, followed by purification on a FLAG-affinity column as described. The activity of the affinity-purified TBSV replicase was tested on the same amount of DI-72(2) RNA added to each sample. DB (panel on the left) and GM (panel on the right) were added in the following amounts: 0, 100, 150, 200, 250 mM for DB and 0, 25, 50, 100, 200 mM for GM. Denaturing PAGE analysis of the 32 P-labeled RNA products obtained with the purified tombusvirus replicase is shown. Note that this replicase preparation is only capable of complementary RNA synthesis on the added template RNA, but incapable of supporting a full cycle of replication. (B) The effect of GM and DB on binding to the viral p33 and p92 proteins in vitro. MBP-tagged p92 and p33 were separately immobilized on amylose beads, followed by incubation in the presence of 0 or 100 mM GM or 150 mM DB with a cytosolic extract prepared from yeast expressing wt eEF1A. The bound eEF1A was eluted from the beads and were analyzed by 10% SDS-PAGE and detected via Western blotting using anti-eEF1A antibody (Top panel). The affinity-purified recombinant MBP-TBSV p92, MBP-TBSV p33 and MBP were analyzed by 10% SDS-PAGE and Coomassie blue-staining (Bottom panel). Found at: doi:10.1371/journal.ppat.1001175.s004 (0.09 MB PDF) The calculation of information and organismal complexity BACKGROUND: It is difficult to measure precisely the phenotypic complexity of living organisms. Here we propose a method to calculate the minimal amount of genomic information needed to construct organism (effective information) as a measure of organismal complexity, by using permutation and combination formulas and Shannon's information concept. RESULTS: The results demonstrate that the calculated information correlates quite well with the intuitive organismal phenotypic complexity defined by traditional taxonomy and evolutionary theory. From viruses to human beings, the effective information gradually increases, from thousands of bits to hundreds of millions of bits. The simpler the organism is, the less the information; the more complex the organism, the more the information. About 13% of human genome is estimated as effective information or functional sequence. CONCLUSIONS: The effective information can be used as a quantitative measure of phenotypic complexity of living organisms and also as an estimate of functional fraction of genome. REVIEWERS: This article was reviewed by Dr. Lavanya Kannan (nominated by Dr. Arcady Mushegian), Dr. Chao Chen, and Dr. ED Rietman (nominated by Dr. Marc Vidal). Organismal complexity is difficult to define and to measure, especially quantitatively. When DNA was discovered to be the material basis of inheritance in all organisms, it was thought that the DNA content of an organism should correlate with its phenotypic complexity, but soon thereafter the C-value paradox was found. C-value refers to the amount of DNA contained within a haploid nucleus, and usually equals to genome size. Salamanders and lungfishes have the largest genomes of 120pg, while the C-value of humans is only 3.5pg [1] . C-values vary enormously among species. In animals they range more than 3,300-fold. Variation in C-values bears no relationship to the complexity of the organism. The discovery of non-coding DNA in the early 1970 s resolved the C-value paradox. Although it is still unclear why some species have a remarkably higher amount of non-coding sequences than others of the same level of complexity, it was believed that the number of genes contained in the genome, rather than the genome size, correlated with the complexity of the organism. However, the human genome project and other model organism genome projects revealed that there are only about 25,000 genes in the human genome [2] , while simple organism nematode have 19,500 genes [3] and rice even has more genes than humans, 46,000~55,000 [4] . Obviously, the number of genes bears no direct relationship to phenotypic complexity. This is called Gvalue paradox.