v-jun avian sarcoma virus 17 oncogene homolog / Jun proto-oncogene, AP-1 transcription factor subunit (JUN) : Time behavioural study of 3rd order combinations in WNT3A stimulated HEK 293 cells

v-jun avian sarcoma virus 17 oncogene homolog / Jun proto-oncogene, AP-1 transcription factor subunit (JUN) : Time behavioural study of 3rd order combinations in WNT3A stimulated HEK 293 cells shriprakash sinha Independent Researcher; Orcid ID : orcid.org/0000-0001-7027-5788 Address : 104-Madhurisha Heights Phase 1, Risali, Bhilai-490006, India Corresponding author email : [email protected] Abstract JUN encode the transcription factor Jun. The structure of activator protein (AP1) is a heterodimer composed of proteins belonging to the c-FOS, c-JUN, ATF and JDP families. Both JUN and its heterodimerization partners in AP1 formation, are subject to regulation by diverse extracellular stimuli, like peptide growth factors, pro-inflammatory cytokines, oxidative and other forms of cellular stress, and UV irradiation. Gujral and MacBeath [1] provides a quantitative, and dynamic study of WNT3A-mediated stimulation of HEK 293 cells, where they record time based expression profiles of several response genes which correlated significantly with proliferation and migration. By monitoring the dynamics of gene expression using self-organizing maps, they identified clusters of genes that exhibit similar expression dynamics and uncovered previously unrecognized positive and negative feedback loops. However, their study depicts/uses singular measurements of individual gene expression at different time snapshots/points to infer the system wide analysis of the pathway. At any particular time point, it is often the case that genes are working synergistically in combinations, even though their expression measurements are singular in nature. Here, I •enumerate and rank all 2415 JUN related 3rd order combinations in a forest of 71C3combinations using four different sensitivity methods; •show the conserved rankings for JUN-X-X combinations, which point to existence of biological synergy of some of these combinations across the different sensitivity methods; and •study the behaviour of some of these combinations related to WNT3A response genes that are ranked by the machine learning search engine (Sinha [2]) in time. Patterns of combinations emerge, some of which have been tested in wet lab, while others require further wet lab analysis. Keywords: Sensitivity analysis, Support vector ranking, Hilbert Schmidt ITime behavioural study of 3-odr JUN comb. in WNT3A stimulated cells 1Aspects of unpublished work were presented in a poster session at Cell Symposia: Technology. Biology. Data Science, 9-11 October 2016, Berkeley, California, USA. Preprint submitted to Preprint March 9, 2025 Independence Criterion indices (HSIC) and Sobol indicies, WNT3A 1. Significance Sinha [2] recently demonstrated the use of machine learning based search engine to rank/reveal gene combinations at 2nd order for the time series data by Gujral and MacBeath [1] and showed how it is possible to locate combinations of priority that might be working synergistically, using sensitivity methods and powerful support vector ranking algorithm. However, the problem explodes combinatorially with even a small set of 71 recorded genes in the study by Gujral and MacBeath [1], when one steps to explore 3rd order combinations. With the total number of 71C3(= 57155) combinations, it becomes nearly impossible for any biologist to study the system wide dynamics of any pathway. Also, the amount of time usually needed to search for and test a combination is far more than the search down by the machine learning based search engine. Here, I extend the research work by Sinha [2] to conduct a behavioral study of 3rd order JUN related combinations using individual gene expressions measured in time, in WNT3A stimulated HEK 293 cells. 2. Introduction The details of the machine learning based search engine has been recently published in Sinha [2] and deployed to explore the 2nd order combinations of genes in the data set provided by Gujral and MacBeath [1]. Nevertheless, here, I point to the fundamentals of the published work for completeness. 2.1. A combinatorial problem Sensitivity analysis plays a major role in computing the strength of the influence of involved factors in any phenomena under investigation. When applied to expression profiles of various intra/extracellular factors that form an integral part of a signaling pathway, the variance and density based analysis yields a range of sensitivity indices for individual as well as various combinations of factors. These combinations denote the higher order interactions among the involved factors. Computation of higher order interactions is often time consuming but it gives a chance to explore the various combinations that might be of interest in the working mechanism of the pathway. For example, in a range of fourth order combinations among the various factors of the Wnt pathway, it would be easy to assess the influence of the destruction complex formed by APC, AXIN, CSKI and GSK3 interaction. But the effect of these combinations vary over time as measurements of fold changes and deviations in fold changes vary. So it is imperative to know how an interaction or a combination of the involved factors behave in time and Sinha [2] develops a procedure to track the behaviour by exploiting the influences of these involved factors. 2 2.2. A possible solution In this work, after estimating the individual effects of factors for a higher order combination, the individual indices are considered as discriminative features. A combination, then, is a feature set in higher order (≥2 ,i.e multivariate). With an excessively large number of factors involved in the pathway, it is difficult to search for important combinations in a wide search space over different orders. Exploiting the analogy with the issues of prioritizing webpages using ranking algorithms, for a particular order, a full set of combinations of interactions can then be prioritized based on these features using a powerful ranking algorithm via support vectors Joachims [3]. Recording the changing rankings of the combinations over time reveals how higher order interactions behave within the pathway and when an intervention might be necessary to influence the interaction within the pathway. 2.3. v-jun avian sarcoma virus 17 oncogene homolog / Jun protooncogene, AP-1 transcription factor subunit (JUN) Maki et al. [4] show that biologically active molecular clones of avian sarcoma virus 17 (ASV 17) contain a replication-defective proviral genome of 3.5 kilobases (kb), that retains partial gag and env sequences, which flank a cell-derived putative oncogene of 0.93 kb, termed jun. jun lacks preserved coding domains of tyrosine-specific protein kinases and the probable transformation-specific protein in ASV 17-transformed cells is a 55-kDa gag-jun fusion product. Angel et al. [5] show that binding of the human transcription factor JUN/AP1 to a conserved 8 bp nucleotide sequence (TRE) is responsible for increased transcription of different cellular genes in response to tumor promoters, such as TPA, and serum factors. Enhanced JUN/AP1 activity in TPA-stimulated cells is regulated by two different mechanisms: a posttranslational event acting on preexisting JUN/AP1 molecules, and transcriptional activation of JUN gene expression leading to an increase in the total amount of JUN/AP1. Their results demonstrated that JUN transcription was directly stimulated by its own gene product. c-JUN was originally isolated as the cellular homolog of v-JUN, as stated in Wisdom et al. [6]. They state that c-JUN is a component of AP1, which is activated by a wide variety of extracellular stimuli. The regulation of c-JUN is complex and involves both increases in the levels of c-JUN protein as well as phosphorylation of specific serines (63 and 73) by JUN N-terminal kinase (JNK). They used fibroblasts derived from c-JUN null embryos to define the role of c-JUN in two separate processes, namely, cell growth and apoptosis. Hess et al. [7] state that The AP1 transcription factor is mainly composed of JUN, FOS and ATF protein dimers. It mediates gene regulation in response to a many physiological and pathological stimuli, including cytokines, growth factors, stress signals, bacterial and viral infections, as well as oncogenic stimuli. I present 3rd order combinations of JUN with other genes, that the machine learning based search engine points to, as possible synergistic combinations that might be working in time. 3 3. Methods Please refer to sections of Sinha [2] for methods, design of study and analysis of data for 2nd order combinations. The same method and design of study is used to generate results for 3rd order combinations presented in this study. 4. Time series data Gujral and MacBeath [1] present a set of 71 WNT-related gene expression values for 6 different times points over a range of 24-hour period using qPCR. The changes represent the fold-change in the expression levels of genes in 200 ng/mL WNT3A-stimulated HEK 293 cells in time relative to their levels in unstimulated, serum-starved cells at 0hour. Gujral and MacBeath [1] state that qPCR data are the means of three biological replicates. Only genes whose mean transcript levels changed by more than two-fold at one or more time points during the 24-hour time course were considered significant. Positive (negative) numbers represent up (down) -regulation. We have already covered the issues related to these data sets in detail in Sinha [8]. Readers are requested to go through them in the pointed reference. The tools of study which are used here have been published in another foundational work in Sinha [8]. 5. Design of experiment 5.1. Pipeline for time series data For the case of time series data, interactions among the contributing factors are studied by comparing triplets of fold-changes at single time points. The prodecure begins with the generation of distribution around measurements at single time points with added noise is done to estimate the indices. A distribution is generated for the fold changes at single time points. Then for every gene, there is a vector of values representing fold changes as well as deviations in fold changes for different time points and durations between time points, respectively. Next a listing of all Cn kcombinations for knumber of genes from a total of ngenes is generated. kis ≥2 and ≤(n−1). Each of the combination of order krepresents a unique set of interaction between the involved genetic factors. After this, the datasets are combined in a specifed format which go as input as per the requirement of a particular sensitivity analysis method. Thus for each pth combination in Cn kcombinations, the dataset is prepared in the required format from the distributions for two separate cases which have been discussed above. (See .R code in mainScript-1-1.R). After the data has been transformed, vectorized programming is employed for density based sensitivity analysis and looping is employed for variance based sensitivity analysis to compute the required sensitivity indices for each of the pcombinations. This procedure is done for different kinds of sensitivity analysis methods. After the above sensitivity indices have been stored for each of the pth combination, the next step in the design of experiment is conducted. Since there is only one 4 recording of sensitivity index per combination, each combination forms a training example which is alloted a training index and the sensitivity indices of the individual genetic factors form the training example. Thus there are Cn ktraining examples for kth order interaction. Using this training set SVMRank learn Joachims [3] is used to generate a model on default value Cvalue of 20. In the current experiment on toy model Cvalue has not been tunned. The training set helps in the generation of the model as the different gene combinations are numbered in order which are used as rank indices. The model is then used to generate score on the observations in the testing set using the SV MRank classi f y Joachims [3]. Note that due to availability of only one example per combination, after the model has been built, the same training data is used as test data to generates the scores. This procedure is executed for each and every sensitivity analysis method. This is followed by sorting of these scores along with the rank indices (i.e the training indices) already assigned to the gene combinations. The end result is a sorted order of the gene combinations based on the ranking score learned by the SV MRank algorithm. Finally, this entire procedure is computed for sensitivity indices generated for each and every fold change at time point and deviations in fold change at different durations. Observing the changing rank of a particular combination at different times and different time periods will reveal how a combination is behaving. Note that the following is the order in which the files should be executed in R, in order, for obtaining the desired results (Note that the code will not be explained here) - • use source(”mainScript-1-1.R”) with arguments for Dynamic data •source(”SVMRankResults-D.R”), to rank the interactions (again this needs to be done separately for different kinds of SA methods), •use source(”Combine-Time-files.R”), if computing indices separately via previous file, •source(”Sort-n-Plot-D.R”) to sort the interactions. Note that the sorting is chages the interaction ranking in time. Thus •use source(”Interaction-Priority-Intime.R”) to find the prioritized ranking of each and every interaction over the different time points and finally •use source(”Print-RankingAND-Interaction-Rank.R”) to print individual ranking of the required input factor with other interaction factors. 6. Results & Discussion 6.1. Time series data by Gujral and MacBeath [1] NOTE - Ranking was assigned on scores that were sorted in DECREASING values. So, 1 was assigned to highest score and vice versa. Results for the 3rd order interactions are presented here. The results first discuss the behaviour of interactions across the snapshots of time using the computed sensitivities on fold change measurements per time snapshot. The analysis was done using 4 different sensitivity indices. Out of the 71C3combinations, I consider/present only those combinations that show a ranking within first 10,000 out of 57,155. This choice is liberal and biologists/oncologists can have a more stricter choice as per need. Two observations are made, •the ranking of a particular combination is conserved (i.e within the 10,000 range) in a particular time point or in the early phase or late phase of WNT3A stimulation, across the majority of the four sensitivity methods, which is a 5 strict criteria of assessment or •the ranking of a particular combination is conserved across time points/phase (i.e they are within the 10,000 range) and the majority of the four sensitivity methods, which is relaxed criteria of assessment. Applying this filter helps reveal important combinations of interest that might be working synergistically at a higher order level in the cell. Regarding technical points of implementation, the rankings were generated without scaling/normalizing the time series data provided by Gujral and MacBeath [1]. For estimating the sensitivity indices, a small gaussian distribution using the function rnorm that generates a vector of normally distributed random variables given a vector length n (here 9, the 10th one is the mean/recorded gene regulation itself), a population mean µand population standard deviation σ. The syntax for using rnorm is as follows: rnorm(n, mean, sd). Further, I use the jitter funtion to add a little bit of noise to the data. This helps to see if the generated rankings are robust or not. 6.2. Enumeration and ranking of 2415 JUN-X-X combinations from Gujral and MacBeath [1] In the supplementary section, I present four files, each containing the rankings of 3rd order combinations, that wary in time (shown for 5 time points). Each file represents the rankings computed using a particular sensitivity method. The changing rankings in time for a particular combination represents the importance of contribution/role that combination plays in the cell stimulated with WNT3A. The sensitivity methods used are Hilbert Schmidt Independence Criterion indices (HSIC) indices (with rbf and linear kernel in Da Veiga [9]) and Sobol indicies (with 2002 implementation in Saltelli [10] and martinez implementation in Martinez [11] and Baudin et al. [12]). 6.3. Conserved machine learning rankings for tested JUN-X-X combinations A total of 2415, 3rd order combinations involving JUN were obtained from a full set of 71C3= 57155 combinations. Further, from this selected set, using the above criteria for conserved rankings, I report/tabulate the meaningful combinations that might be working synergistically. Tables 2, 3 and 4 show the rankings for the same combinations as in table 1, but using rbf kernel for HSIC, 2002 implementation for SOBOL and martinez implementation for SOBOL, respectively. As one tallies the rankings of across these tables for a particular combination, one finds that the role of the combination of interest is conserved. This conservation points to the existence of the biological synergy, whether the combination has been tested or unexplored/untested. 6.3.1. Examining the behaviour of FOSL1-JUN-X combinations The FOS and JUN families of eukaryotic transcription factors heterodimerize to form complexes capable of binding 5’-TGAGTCA-3’ DNA elements. Glover and Harrison [13] determined the X-ray crystal structure of a heterodimer of the bZIP regions of c-FOS and c-JUN bound to DNA. Both subunits formed continuous α-helices. The 6 RANKING @tiUSING HSIC - LINEAR 3rd order comb. t1t3t6t12 t24 3rd order comb. t1t3t6t12 t24 DKK1-JUN-SENP2 3 13146 45291 34681 42815 FZD5-JUN-TLE2 33 2696 2557 55511 23342 DVL2-JUN-SENP2 40 7571 46728 17699 4151 DKK1-JUN-LRP5 48 627 56508 43115 37922 DVL2-JUN-TCF7L1 50 34646 43296 24980 5047 DKK1-JUN-SFRP4 53 1275 44566 37789 42099 DKK1-JUN-TLE2 55 1113 26078 37591 53405 DKK1-JUN-WNT2B 56 5221 53944 55625 44612 DKK1-JUN-WNT2 58 1936 43652 35916 55311 DKK1-JUN-TCF7L1 67 33647 49514 43728 45939 FZD5-JUN-WNT2 71 4401 38543 47328 33190 FZD5-JUN-WNT4 79 8704 42294 52216 15657 DVL2-JUN-TLE2 87 42627 5285 18305 31287 FZD5-JUN-KREMEN1 96 24278 50801 44288 10781 FZD5-JUN-FBXW4 97 13039 25922 48154 41051 FZD5-JUN-RHOU 105 12942 56571 25707 3718 FRZB-JUN-SENP2 109 12704 33983 8160 2937 CTNNBIP1-JUN-RHOU 119 11333 54553 37428 52492 DKK1-JUN-FBXW4 129 11896 24951 31819 36572 DVL2-JUN-FBXW4 135 26880 12581 12861 8554 DVL2-JUN-KREMEN1 178 24966 37758 33223 9256 DVL2-JUN-WNT4 203 51324 39998 14159 3459 CTNNBIP1-JUN-WNT2 206 3834 45427 33327 6238 DKK1-JUN-RHOU 210 3670 42736 27568 47765 DKK1-JUN-PYGO1 218 3236 51191 53120 2659 CTNNBIP1-JUN-PPP2R1A 222 17930 41664 52992 44848 CTNNBIP1-JUN-KREMEN1 241 6571 55388 29592 14471 DVL2-JUN-WNT2 252 43710 32464 4614 34311 DKK1-JUN-PPP2R1A 267 12255 56230 48454 54215 CTNNBIP1-JUN-SFRP4 282 1303 44436 32290 6337 FZD5-JUN-WNT5A 284 6962 43259 53869 10481 DKK1-JUN-WNT3A 289 6120 44241 52638 12402 DVL2-JUN-PITX2 293 27343 32163 42607 21387 DVL2-JUN-TLE1 306 36089 30012 17193 22195 DKK1-JUN-WNT4 316 926 46570 28834 28365 DVL2-JUN-WNT3A 322 31939 32028 29113 4760 DKK1-JUN-TCF7 337 19121 54724 39273 38745 FZD5-JUN-PYGO1 348 1924 32815 54426 36260 DVL2-JUN-WNT2B 350 44599 38931 37935 16078 FZD5-JUN-TCF7 367 15943 33055 41015 49415 DKK1-JUN-PPP2CA 408 27394 50340 28816 37806 DKK1-JUN-TLE1 417 16467 28915 26740 32148 EP300-JUN-KREMEN1 445 18545 22047 46724 18178 FZD5-JUN-TLE1 448 23448 36104 54093 45715 CTNNBIP1-JUN-SENP2 451 45193 55478 33408 6827 FOSL1-JUN-SENP2 458 25557 50663 10786 1378 FRZB-JUN-WNT2 478 2085 21294 5583 18722 DVL2-JUN-PPP2CA 504 43997 37157 2445 3613 DVL2-JUN-TCF7 544 30871 41999 26197 8304 CTNNBIP1-JUN-PITX2 546 6389 45937 54346 11119 DVL2-JUN-PPP2R1A 555 45651 45029 17035 30388 JUN-PYGO1-WNT3A 570 14118 6423 19469 36536 DKK1-JUN-LRP6 617 2273 42860 25885 1791 FZD5-JUN-SLC9A3R1 625 5957 34667 52133 12374 CTNNBIP1-JUN-TCF7 674 24941 33229 25262 14247 FRAT1-JUN-WNT2 676 35197 23478 4515 23224 DVL1-JUN-WNT2B 696 13741 48925 47783 49704 CTNNBIP1-JUN-LRP5 697 1403 32050 45845 13691 FRAT1-JUN-PITX2 748 50033 38113 50412 44660 CXXC4-JUN-TLE2 764 1040 837 11709 30876 DVL2-JUN-WIF1 788 37918 18319 11932 34672 FBXW11-JUN-WNT2B 795 49304 52661 53929 54016 FBXW2-JUN-WNT4 806 26430 56620 37987 55952 FZD8-JUN-WNT2B 814 45692 37162 26955 54126 CSNK1D-JUN-LEF1 823 6859 47543 11454 29458 CXXC4-JUN-SENP2 843 21048 50347 6595 9660 CSNK1G1-JUN-SENP2 855 23957 55112 11084 3256 DVL2-JUN-WNT5A 871 37929 52159 30056 48277 FRAT1-JUN-SENP2 876 27146 34459 14780 13983 CXXC4-JUN-RHOU 881 1789 43156 41625 53423 FBXW11-JUN-LRP5 885 23634 45785 27639 45330 FZD1-JUN-WNT2 886 20644 39928 4484 8707 BCL9-JUN-TCF7L1 889 18626 55169 44931 2804 DKK1-JUN-PITX2 913 6407 42538 52798 634 FRZB-JUN-TCF7L1 932 26973 39828 31513 3210 DKK1-JUN-SFRP1 961 1935 26970 33204 47981 FBXW11-JUN-SFRP4 964 21656 28145 38980 53582 CXXC4-JUN-LRP5 971 1353 33173 6860 26690 FOSL1-JUN-TCF7 996 16387 31797 50574 23742 FOSL1-JUN-TCF7L1 1000 17132 38816 29827 1621 FZD1-JUN-TLE2 1075 7630 4614 20083 41713 FBXW11-JUN-SENP2 1078 21114 46139 41233 39344 CSNK1G1-JUN-WNT2 1087 1305 52762 5894 31347 CTNNBIP1-JUN-WNT3A 1110 7698 46119 54862 31125 CSNK1G1-JUN-TCF7L1 1134 10933 47748 13909 25134 CXXC4-JUN-FBXW4 1138 13192 17971 6537 17461 DVL2-JUN-SFRP1 1150 43616 21933 13995 37221 DAAM1-JUN-WNT2B 1152 51606 37010 32012 42370 CTNNBIP1-JUN-PPP2CA 1160 17287 25595 27276 6859 FRAT1-JUN-SFRP4 1177 38200 26202 16198 34929 CCND1-JUN-SFRP4 1212 40676 36610 54521 54939 CTNNBIP1-JUN-SLC9A3R1 1227 27649 37384 31940 7577 FZD7-JUN-WNT3A 1250 17078 32637 21100 43381 FBXW2-JUN-SENP2 1253 32758 51631 42897 55749 CCND1-JUN-PITX2 1260 51205 42011 18763 52917 GSK3B-JUN-TLE1 1271 40084 30251 26212 40565 FBXW11-JUN-TLE2 1285 29879 11548 36884 55887 CXXC4-JUN-SFRP4 1308 4014 25558 7639 24982 CTNNBIP1-JUN-FBXW4 1320 15975 24670 37193 14093 DIXDC1-JUN-FBXW4 1340 27624 17009 49472 50306 JUN-PYGO1-TLE2 1341 24994 40582 4657 37476 BCL9-JUN-TLE2 1353 1767 14711 51640 5284 CCND3-JUN-PYGO1 1362 50934 48125 55357 25009 CSNK1G1-JUN-TLE2 1365 2675 25875 17296 52928 CXXC4-JUN-TCF7 1379 21025 34076 34379 37036 FRZB-JUN-PPP2CA 1383 13534 31714 933 1610 DIXDC1-JUN-TCF7L1 1397 18158 39442 41838 15514 DKK1-JUN-LEF1 1407 345 39847 38268 15426 FRZB-JUN-SLC9A3R1 1409 6059 10710 25355 42497 FOSL1-JUN-PITX2 1479 1306 37107 54515 12375 FZD1-JUN-SFRP4 1493 24355 34044 13135 44616 CXXC4-JUN-PYGO1 1496 10929 38139 43065 17470 CTNNBIP1-JUN-LRP6 1499 4675 42275 26834 8608 CCND1-JUN-PPP2CA 1525 10554 35624 43398 54711 FBXW11-JUN-TCF7L1 1526 26632 46567 48986 51386 FOSL1-JUN-WNT3A 1542 4890 20754 29478 5342 CXXC4-JUN-TCF7L1 1561 16594 47993 27451 26786 CSNK1G1-JUN-KREMEN1 1571 14622 52390 27682 7035 CTBP2-JUN-TLE2 1591 46301 4452 35914 13872 CSNK1A1-JUN-TCF7L1 1599 2840 51813 45452 5619 CTNNBIP1-JUN-WNT4 1605 6379 54822 28948 10594 FRAT1-JUN-TCF7L1 1626 39276 40450 30425 12391 DVL1-JUN-SENP2 1636 27735 49539 26023 46168 FZD1-JUN-WNT2B 1648 10746 47422 41725 9336 BCL9-JUN-RHOU 1653 6622 56085 44704 6331 DAAM1-JUN-SENP2 1658 50069 38838 15921 52559 Table 1: Rankings of JUN-X-X. A list of approximately first 125 combinations with rankings below 10,000 out of 57,155. SA - HSIC; Kernel - linear carboxy-terminal regions form an asymmetric coiled-coil, and the amino-terminal regions make base-specific contacts with DNA in the major groove. Comparison of the two crystallographically distinct protein-DNA complexes showed that the coiled-coil 7 RANKING @tiUSING HSIC - RBF 3rd order comb. t1t3t6t12 t24 3rd order comb. t1t3t6t12 t24 DKK1-JUN-SENP2 2445 33296 14766 10519 28087 FZD5-JUN-TLE2 18001 2899 23629 42402 48124 DVL2-JUN-SENP2 4462 28972 39208 37581 33219 DKK1-JUN-LRP5 44363 59 7957 31836 12454 DVL2-JUN-TCF7L1 6692 37689 42883 22632 2352 DKK1-JUN-SFRP4 23984 4600 8391 10229 3109 DKK1-JUN-TLE2 10461 10318 33449 28447 40483 DKK1-JUN-WNT2B 23590 25652 38169 27335 22936 DKK1-JUN-WNT2 15958 5371 10742 16568 29068 DKK1-JUN-TCF7L1 11024 26336 26266 38929 770 FZD5-JUN-WNT2 45453 4822 16137 45403 40375 FZD5-JUN-WNT4 28544 6905 45357 25315 15393 DVL2-JUN-TLE2 6307 41319 43004 40157 41574 FZD5-JUN-KREMEN1 14265 7847 49848 50707 31671 FZD5-JUN-FBXW4 32588 11252 24483 51441 24264 FZD5-JUN-RHOU 21830 6512 2365 50002 36411 FRZB-JUN-SENP2 1481 18469 38799 27435 28090 CTNNBIP1-JUN-RHOU 47402 8172 34623 51918 36687 DKK1-JUN-FBXW4 36904 13586 2374 17612 12759 DVL2-JUN-FBXW4 26608 26616 1444 12875 15856 DVL2-JUN-KREMEN1 13103 30709 32743 48017 27397 DVL2-JUN-WNT4 21779 49475 22727 20132 5205 CTNNBIP1-JUN-WNT2 42601 8719 44457 18821 49158 DKK1-JUN-RHOU 4232 243 27543 37520 46403 DKK1-JUN-PYGO1 35611 92 8244 34065 42310 CTNNBIP1-JUN-PPP2R1A 42662 30325 24952 5762 37211 CTNNBIP1-JUN-KREMEN1 49360 1571 43983 55548 30690 DVL2-JUN-WNT2 26710 49937 37500 33239 22813 DKK1-JUN-PPP2R1A 19726 15606 1085 29841 36603 CTNNBIP1-JUN-SFRP4 50889 5964 52857 23302 32122 FZD5-JUN-WNT5A 8780 13834 37545 56636 50500 DKK1-JUN-WNT3A 10634 402 10397 46299 3270 DVL2-JUN-PITX2 22623 16521 37051 52719 15020 DVL2-JUN-TLE1 36629 36442 30000 29148 8644 DKK1-JUN-WNT4 8806 34 14859 3085 9371 DVL2-JUN-WNT3A 25797 23440 31750 21568 1485 DKK1-JUN-TCF7 4445 24804 23041 23852 12528 FZD5-JUN-PYGO1 13399 522 43506 36219 51123 DVL2-JUN-WNT2B 35904 41234 30718 47010 18770 FZD5-JUN-TCF7 13732 2579 35094 27662 15659 DKK1-JUN-PPP2CA 872 31181 33266 21737 30431 DKK1-JUN-TLE1 12635 18611 25341 28339 18891 EP300-JUN-KREMEN1 4639 142 27356 54948 19911 FZD5-JUN-TLE1 12747 18718 33701 39270 7010 CTNNBIP1-JUN-SENP2 42259 50095 40291 21021 34386 FOSL1-JUN-SENP2 15271 29847 41615 22047 48378 FRZB-JUN-WNT2 21990 24790 40993 7840 23831 DVL2-JUN-PPP2CA 12969 55374 21200 14940 32734 DVL2-JUN-TCF7 4906 31956 33672 6793 3595 CTNNBIP1-JUN-PITX2 55688 6273 51543 54725 26305 DVL2-JUN-PPP2R1A 7790 48428 6855 9490 40633 JUN-PYGO1-WNT3A 10181 579 35737 33610 43746 DKK1-JUN-LRP6 26624 5079 13887 46906 27696 FZD5-JUN-SLC9A3R1 39777 3230 20742 34190 14401 CTNNBIP1-JUN-TCF7 41380 25473 25735 11678 41440 FRAT1-JUN-WNT2 21621 33205 53792 38197 10593 DVL1-JUN-WNT2B 44382 6721 23326 56398 1235 CTNNBIP1-JUN-LRP5 51735 260 35013 50048 34138 FRAT1-JUN-PITX2 28349 55075 50998 56838 16856 CXXC4-JUN-TLE2 2337 10507 41107 15818 46481 DVL2-JUN-WIF1 6060 40504 15256 30934 48673 FBXW11-JUN-WNT2B 30736 52338 1286 29236 8641 FBXW2-JUN-WNT4 49067 9843 17416 10298 1111 FZD8-JUN-WNT2B 30397 45061 16498 26458 9398 CSNK1D-JUN-LEF1 20901 8723 38740 12713 27687 CXXC4-JUN-SENP2 1851 32478 55139 8858 43014 CSNK1G1-JUN-SENP2 2057 43819 27038 14070 17638 DVL2-JUN-WNT5A 16054 35608 35930 17120 44512 FRAT1-JUN-SENP2 8350 32873 42151 5535 36295 CXXC4-JUN-RHOU 7270 2533 37155 46380 45935 FBXW11-JUN-LRP5 46395 5177 29373 22491 4533 FZD1-JUN-WNT2 52622 26168 48248 5592 27125 BCL9-JUN-TCF7L1 24868 22870 36874 19513 1734 DKK1-JUN-PITX2 24208 3989 4050 56945 15274 FRZB-JUN-TCF7L1 9523 51903 25105 20905 20981 DKK1-JUN-SFRP1 15339 875 11803 12204 51585 FBXW11-JUN-SFRP4 17788 9290 3063 40195 1563 CXXC4-JUN-LRP5 15539 1611 30933 39991 28813 FOSL1-JUN-TCF7 18538 5069 12539 42545 29271 FOSL1-JUN-TCF7L1 5134 9823 24616 52464 27691 FZD1-JUN-TLE2 24688 27343 11195 3015 35208 FBXW11-JUN-SENP2 2521 15541 36470 25945 625 CSNK1G1-JUN-WNT2 10147 5580 32401 33214 37290 CTNNBIP1-JUN-WNT3A 24780 5944 45858 50803 13854 CSNK1G1-JUN-TCF7L1 827 11310 28918 27910 3674 CXXC4-JUN-FBXW4 14457 30498 1036 36322 33651 DVL2-JUN-SFRP1 10995 46091 46482 41358 52216 DAAM1-JUN-WNT2B 34628 49211 11090 56716 4721 CTNNBIP1-JUN-PPP2CA 38196 36635 20141 33944 38991 FRAT1-JUN-SFRP4 35091 47221 26189 44148 8318 CCND1-JUN-SFRP4 38237 25562 52223 10931 1352 CTNNBIP1-JUN-SLC9A3R1 45992 37553 52601 42751 21986 FZD7-JUN-WNT3A 6578 3907 45657 38691 15081 FBXW2-JUN-SENP2 25289 51870 3972 20307 1098 CCND1-JUN-PITX2 44312 43519 25962 49672 2955 GSK3B-JUN-TLE1 21678 43855 47673 19227 7501 FBXW11-JUN-TLE2 12624 12939 27323 12238 19853 CXXC4-JUN-SFRP4 8489 12877 51306 12233 26552 CTNNBIP1-JUN-FBXW4 38357 26382 25017 7941 22281 DIXDC1-JUN-FBXW4 53699 39669 27414 16988 3729 JUN-PYGO1-TLE2 2091 9953 10078 26860 57045 BCL9-JUN-TLE2 25015 9243 46821 14241 21549 CCND3-JUN-PYGO1 15052 38950 15637 52389 3265 CSNK1G1-JUN-TLE2 3633 15390 39684 2796 27092 CXXC4-JUN-TCF7 2896 16477 22826 15141 21339 FRZB-JUN-PPP2CA 5873 49297 3845 20493 26715 DIXDC1-JUN-TCF7L1 36423 32144 31736 45585 462 DKK1-JUN-LEF1 15292 323 25256 25883 39611 FRZB-JUN-SLC9A3R1 34630 15041 47309 7650 16482 FOSL1-JUN-PITX2 42099 14135 52254 57017 24935 FZD1-JUN-SFRP4 44475 27425 5889 28115 8946 CXXC4-JUN-PYGO1 15268 3842 31367 43633 53074 CTNNBIP1-JUN-LRP6 41800 8865 4751 4915 48545 CCND1-JUN-PPP2CA 40595 14062 3971 9088 1571 FBXW11-JUN-TCF7L1 5238 17905 26014 9636 4500 FOSL1-JUN-WNT3A 37744 27522 48171 53533 24924 CXXC4-JUN-TCF7L1 5069 16399 50288 29076 25853 CSNK1G1-JUN-KREMEN1 6491 2240 25073 41585 18357 CTBP2-JUN-TLE2 2322 40968 49108 5379 22516 CSNK1A1-JUN-TCF7L1 22985 1629 17522 50991 17011 CTNNBIP1-JUN-WNT4 39260 388 36889 17634 53412 FRAT1-JUN-TCF7L1 25869 45197 28755 12226 10788 DVL1-JUN-SENP2 17916 15346 45039 2157 2784 FZD1-JUN-WNT2B 49546 6083 15156 54576 28886 BCL9-JUN-RHOU 27668 3483 7713 42147 31193 DAAM1-JUN-SENP2 28479 51658 5776 9253 6064 Table 2: Rankings of JUN-X-X. A list of approximately first 125 combinations with rankings below 10,000 out of 57,155. SA - HSIC; Kernel - rbf is flexibly joined to the basic regions and that the FOS-JUN heterodimer did not recognize the asymmetric 5’-TGAGTCA-3’ recognition element in a unique orientation. Heterodimerization among the basic-leucine zipper (bZIP) proteins or among the basic-helixloophelix-leucine zipper (bHLHZip) proteins confers a multitude of combi8 RANKING @tiUSING SOBOL - 2002 3rd order comb. t1t3t6t12 t24 3rd order comb. t1t3t6t12 t24 DKK1-JUN-SENP2 754 9372 11904 1076 33385 FZD5-JUN-TLE2 41573 48046 35361 54860 7334 DVL2-JUN-SENP2 13471 27115 21910 19735 56433 DKK1-JUN-LRP5 48850 11594 39630 41378 23052 DVL2-JUN-TCF7L1 31682 50919 38373 29294 10924 DKK1-JUN-SFRP4 2159 46694 9618 10954 53360 DKK1-JUN-TLE2 51285 19906 29994 46512 5324 DKK1-JUN-WNT2B 55363 40120 46822 38204 3471 DKK1-JUN-WNT2 1793 17173 10372 18936 53659 DKK1-JUN-TCF7L1 54195 13967 44741 41708 6796 FZD5-JUN-WNT2 5734 51317 12612 516 52072 FZD5-JUN-WNT4 10431 52363 25511 23980 54325 DVL2-JUN-TLE2 37775 50662 42118 36079 5151 FZD5-JUN-KREMEN1 40950 45002 28772 48247 9854 FZD5-JUN-FBXW4 38132 1495 38878 55550 15245 FZD5-JUN-RHOU 34450 36279 38790 52137 4153 FRZB-JUN-SENP2 12004 43333 28019 17227 24299 CTNNBIP1-JUN-RHOU 42622 37205 47514 55158 1108 DKK1-JUN-FBXW4 55004 10538 47561 46222 3807 DVL2-JUN-FBXW4 37995 50015 47979 42759 40551 DVL2-JUN-KREMEN1 30808 34898 33501 52840 6443 DVL2-JUN-WNT4 16345 10299 13394 21121 55056 CTNNBIP1-JUN-WNT2 11911 1262 6891 21217 41714 DKK1-JUN-RHOU 36718 6757 39502 48964 14725 DKK1-JUN-PYGO1 20453 50366 17707 8188 42484 CTNNBIP1-JUN-PPP2R1A 55954 42703 38291 39039 13787 CTNNBIP1-JUN-KREMEN1 42377 46499 47863 48423 9908 DVL2-JUN-WNT2 16689 9003 10414 13155 52714 DKK1-JUN-PPP2R1A 57057 38094 40889 35645 26618 CTNNBIP1-JUN-SFRP4 16570 24584 750 1029 26322 FZD5-JUN-WNT5A 46652 4870 31639 33192 2907 DKK1-JUN-WNT3A 51531 12300 46409 53700 3796 DVL2-JUN-PITX2 23671 1038 12434 27999 54466 DVL2-JUN-TLE1 19381 6455 15016 21061 52059 DKK1-JUN-WNT4 2160 6260 8008 12977 38088 DVL2-JUN-WNT3A 35727 49416 40820 44967 1537 DKK1-JUN-TCF7 2980 42733 12423 15481 50307 FZD5-JUN-PYGO1 22701 20169 18383 5021 52969 DVL2-JUN-WNT2B 40463 48141 46668 43995 4463 FZD5-JUN-TCF7 21221 30391 25873 1692 44909 DKK1-JUN-PPP2CA 98 19110 16349 21529 30627 DKK1-JUN-TLE1 5879 37800 27150 10679 51804 EP300-JUN-KREMEN1 11605 22398 6349 16123 55238 FZD5-JUN-TLE1 15555 9196 21799 2297 49839 CTNNBIP1-JUN-SENP2 15007 40205 17451 2535 40407 FOSL1-JUN-SENP2 51877 55400 52885 34018 3734 FRZB-JUN-WNT2 18619 2162 17358 26907 22142 DVL2-JUN-PPP2CA 24259 24689 15208 7592 48248 DVL2-JUN-TCF7 25445 6256 18825 27882 46274 CTNNBIP1-JUN-PITX2 11329 1937 10201 6114 40219 DVL2-JUN-PPP2R1A 32860 32858 41918 49574 8979 JUN-PYGO1-WNT3A 1610 17601 24757 13846 37085 DKK1-JUN-LRP6 889 49598 15333 19395 28530 FZD5-JUN-SLC9A3R1 19660 8438 20540 9033 50969 CTNNBIP1-JUN-TCF7 6098 7522 16157 8323 52544 FRAT1-JUN-WNT2 8549 16613 14863 6104 42450 DVL1-JUN-WNT2B 55129 18060 30213 42553 11665 CTNNBIP1-JUN-LRP5 52013 50795 51766 42741 16689 FRAT1-JUN-PITX2 19630 54721 9834 10848 22067 CXXC4-JUN-TLE2 47401 2576 46879 53365 10616 DVL2-JUN-WIF1 15451 4813 8548 10559 52944 FBXW11-JUN-WNT2B 29211 26070 34684 38249 15818 FBXW2-JUN-WNT4 6945 6699 21970 13741 36379 FZD8-JUN-WNT2B 53721 5288 39583 33282 9288 CSNK1D-JUN-LEF1 25658 26247 28008 9195 29514 CXXC4-JUN-SENP2 8825 8401 12932 7871 27023 CSNK1G1-JUN-SENP2 49955 51075 54767 43231 2180 DVL2-JUN-WNT5A 40789 46792 43770 36077 2170 FRAT1-JUN-SENP2 10491 7985 11945 814 56174 CXXC4-JUN-RHOU 43332 26892 49071 46614 1986 FBXW11-JUN-LRP5 29144 55408 44273 48284 18254 FZD1-JUN-WNT2 22633 26709 17508 18911 53158 BCL9-JUN-TCF7L1 10128 54591 19355 15272 44855 DKK1-JUN-PITX2 2939 11664 23494 19389 44598 FRZB-JUN-TCF7L1 43224 53526 30364 36886 9096 DKK1-JUN-SFRP1 56402 47506 45269 56075 23790 FBXW11-JUN-SFRP4 26958 10929 24740 8133 48845 CXXC4-JUN-LRP5 33040 7608 43755 38567 13643 FOSL1-JUN-TCF7 49067 35754 42264 40921 9123 FOSL1-JUN-TCF7L1 4213 41297 24152 15364 47738 FZD1-JUN-TLE2 44268 55094 42586 33377 6664 FBXW11-JUN-SENP2 27619 7495 18431 13804 56624 CSNK1G1-JUN-WNT2 43215 54139 50622 48011 1250 CTNNBIP1-JUN-WNT3A 47078 14611 51686 48296 5008 CSNK1G1-JUN-TCF7L1 6017 14337 20145 21380 48232 CXXC4-JUN-FBXW4 49484 2831 37278 49282 3845 DVL2-JUN-SFRP1 43635 30176 35239 37444 736 DAAM1-JUN-WNT2B 52248 43893 48230 50763 39740 CTNNBIP1-JUN-PPP2CA 1200 14488 18797 18145 43428 FRAT1-JUN-SFRP4 21027 9576 20703 24611 44741 CCND1-JUN-SFRP4 20932 24429 19033 3104 41522 CTNNBIP1-JUN-SLC9A3R1 22481 35127 9927 24826 33487 FZD7-JUN-WNT3A 1386 53880 25449 20632 45908 FBXW2-JUN-SENP2 10475 4057 14601 2973 45279 CCND1-JUN-PITX2 17592 41812 11511 4995 53682 GSK3B-JUN-TLE1 8247 452 12235 2187 37512 FBXW11-JUN-TLE2 28842 50663 44769 54898 3936 CXXC4-JUN-SFRP4 7686 54368 19771 7870 53296 CTNNBIP1-JUN-FBXW4 40631 32924 56400 56117 31184 DIXDC1-JUN-FBXW4 23517 23502 15073 18409 44877 JUN-PYGO1-TLE2 3800 11209 18229 255 32111 BCL9-JUN-TLE2 3148 9305 24717 4483 54658 CCND3-JUN-PYGO1 25910 36673 28134 15173 40843 CSNK1G1-JUN-TLE2 6833 1066 4928 11587 56004 CXXC4-JUN-TCF7 1115 20606 6634 9559 44618 FRZB-JUN-PPP2CA 7300 14667 7614 23131 10832 DIXDC1-JUN-TCF7L1 9143 45568 15142 2009 35636 DKK1-JUN-LEF1 8362 45451 17549 15763 34051 FRZB-JUN-SLC9A3R1 21722 36003 21129 27499 26935 FOSL1-JUN-PITX2 29544 47341 44123 52018 7644 FZD1-JUN-SFRP4 9479 1152 20120 8827 46342 CXXC4-JUN-PYGO1 13879 27252 8058 10543 55180 CTNNBIP1-JUN-LRP6 16607 13114 2882 13685 40184 CCND1-JUN-PPP2CA 23078 52819 9647 2403 50956 FBXW11-JUN-TCF7L1 29061 55371 38660 56451 2416 FOSL1-JUN-WNT3A 10579 5753 10670 19639 21636 CXXC4-JUN-TCF7L1 56040 37157 50497 47616 12624 CSNK1G1-JUN-KREMEN1 6923 4884 26325 13483 55790 CTBP2-JUN-TLE2 45238 40887 44003 32561 49556 CSNK1A1-JUN-TCF7L1 48736 28417 29151 42720 4277 CTNNBIP1-JUN-WNT4 18138 13025 5771 2388 39991 FRAT1-JUN-TCF7L1 43935 48115 50408 53433 8865 DVL1-JUN-SENP2 1057 37410 27437 23571 26894 FZD1-JUN-WNT2B 34517 30754 39634 38168 4014 BCL9-JUN-RHOU 13091 32869 21205 19079 54663 DAAM1-JUN-SENP2 17437 48030 18701 23987 45424 Table 3: Rankings of JUN-X-X. A list of approximately first 125 combinations with rankings below 10,000 out of 57,155. SA - SOBOL; Implementation - 2002 national activities to these transcription factors. To further examine the function of the bHLHZip protein, USF, Pognonec et al. [14] found cellular bZip protein, FRA1/FOSL1 to directly interact with USF using the yeast two-hybrid system. Expression of exogenous USF led to a decrease in AP1-dependent transcription in F9 cells and co9