Credit assignment (CA) to relevant actions poses a challenge because one is often flooded with reward feedback that is not easily causally attributed. We addressed this issue in a reinforcement learning framework wherein choice is mutually controlled by value-caching model-free (MF) and prospective, planning model-based (MB) systems. We find knowledge, stored in a cognitive map, filters exuberant reward feedback to guide CA in both systems but based on different attribute dimensions. In MF, CA is boosted for outcomes that are relevant  to one’s choice, whereas in MB, CA is enhanced for outcomes that attract greater attention during the deliberation process that preceded a choice. We consider normative and mechanistic accounts, including how these processes are instrumental to adaptation. An influential reinforcement learning framework proposes that behavior is jointly governed by model-free (MF) and model-based (MB) controllers. The former learns the values of actions directly from past encounters, and the latter exploits a cognitive map of the task to calculate these prospectively. Considerable attention has been paid to how these systems interact during choice, but how and whether knowledge of a cognitive map contributes to the way MF and MB controllers assign credit  remains underexplored. Here, we examine such sophisticated credit assignment using a dual-outcome bandit task. We provide evidence that knowledge of a cognitive map influences credit assignment in both MF and MB systems, mediating subtly different aspects of apparent relevance. Specifically, we show MF credit assignment is enhanced for those rewards that are related to a choice, and this contrasted with choice-unrelated rewards that reinforced subsequent choices negatively. This modulation is only possible based on knowledge of task structure. On the other hand, MB credit assignment was boosted for outcomes that impacted on differences in values between offered bandits. We consider mechanistic accounts and the normative status of these findings. We suggest the findings extend the scope and sophistication of cognitive map-based credit assignment during reinforcement learning, with implications for understanding behavioral control. An extensive body of psychological and neuroscientific literature on dual-system reinforcement learning (RL) indicates that behavior is governed by two distinct systems –17—a rigHere, we consider two potential complementary CM-based modulators of CA. Both concern the causal structure of the relationship between options and outcomes. One involves the “relatedness” of actual outcomes to an enacted choice, a retrospective effect of a CM on MF CA. The second involves the “importance” of potential outcomes during the deliberation process preceding a choice, a prospective effect of a CM on MB CA.“Relatedness” arises out of a complexity in assigning credit when information about streams of rewards is provided that depends only partly on the actions taken . An MF system, lacking structural causal knowledge, is disposed to assign credit naively to a choice based on the entire collection of ensuing outcomes, irrespective of whether these outcomes were caused by, or related to, an actual initiating action choice. By contrast, knowledge stored as a CM can guide MF CA to favor action-related outcomes.Take an example of a trader who deliberates purchasing one of two available mutual funds: X, which invests in companies A and B, or Y, which invests in companies A and C. Assume the trader opts for X and then later receives positive information about companies B and D. The trader might assign credit in an MF manner to her/his past action (“buy X”), updating the action’s cached value on the basis that positive consequences followed that choice. However, only one component of those positive consequences (that concerning company B) actually related to the choice of fund X. We propose that MF CA is modulated by a CM such that a change in the action’s value will be affected mostly by information about company B. More generally, relatedness depends on a causal attribution of rewards to actions .We consider a second modulator of CA, termed “importance,” as a form of attentional effect. When deliberating between several choice options, and taking into account their prospective outcomes, it is often the case that certain outcomes (which we dub “unimportant”) should not determine choice, as they are common to all choice options. In contrast, other (“important”) outcomes are distinctive to some choice options but not to others, and these should be the main determinants of choice. A CM will contain this type of information and direct attention to the latter alone. We consider the possibility that when the outcomes of the choice are observed, those that garnered more attention at choice are favored in learning.Consider our previous example where information about companies B and D triggers a CA process that leads to positive revaluation of these companies—a process useful for future MB financial decisions related to these companies. We propose this CA process can be biased by CM-based deliberations during choice. Notably, the values of companies B and C were “important” in the trader’s MB deliberation process (choosing a fund), as each is unique to one fund. The values of companies A and D, on the other hand, are less important, as these are either common to both choice options (A) or altogether absent (D). We hypothesize that representations of “important” components in a CM are activated more strongly during choice, leading to them being revalued more when information about choice outcomes are subsequently realized. Thus, ceteris paribus, the increase in the trader’s evaluation of company B will be higher than for company D, given the positive information. This evaluation is then exploited by MB planning processes for future choices.To test these hypotheses, we developed a variant of our previously described dual-outcome bandit task . ParticiIn support of our hypothesis that MFCA is guided by a CM, we found evidence that credit for choice-related and -unrelated outcomes is assigned to actions in a different manner. We show information about rewards actually related to chosen actions alone positively impact on the value of those actions. Information about rewards not related to chosen actions, on the other hand, have an opposite effect. Second, we found that MBCA was greater for choice outcomes that were “important” compared to “unimportant” during choice deliberations. We discuss mechanistic and normative accounts of these results.We designed a full-feedback variant of a dual-outcome bandit task . The tasSI Appendix, Fig. S1), encouraging participants to learn continuously which actions are better. Participants were informed that observing all four vegetables could inform them about market demands but that their earnings on a trial would be based exclusively on the pair of vegetables grown by the person they chose. Subjects were instructed that their goal was to maximize their earnings. Participants earned a notional £1 per choice-related sold vegetable (and £0 per nonsold or choice-unrelated vegetable). Crucially, the reward-feedback stage did not provide an explicit indication about which vegetables were choice related or the notional earnings on that trial. Participants could, however, infer both of these based on exploiting an internal-task transition-structure model , which they learned during training. Henceforth, we refer to sold/unsold vegetables as rewarded/unrewarded, disregarding whether they were choice related or unrelated.Following training, each participant played 392 bandit trials. On each trial, subjects were given 750 ms to make a choice between a random pair of individuals who shared one vegetable as an outcome (and had one other unique vegetable outcome). Next, all four vegetables  were presented, one after the other in a random order, and participants were informed whether each vegetable had sold B. Acrosst(41) = 6.79, P = 3e-8). In comparison, the calculated accuracy rate achieved by an optimal Bayesian learner was 0.82 . To obtain a more fine-grained performance measure, which controls for trial difficulty, for each participant, we ran a logistic regression wherein the chosen display side  was regressed on the contrast (Right − Left) in generating reward probabilities for the two offered persons. This measure, which we term “choice sensitivity,” was positive across participants  = 6.36; P = 1e-7). Additionally, choice sensitivity and accuracy strongly correlated . We acknowledge our task was difficult based on the across-trials average absolute difference in generating reward probabilities between pairs of offered persons (a measure of choice difficulty) varying across participants in the range 0.075 to 0.156, with a mean of 0.123. The upshot is that despite this high task difficulty, participants nevertheless assigned credit in a manner that fostered reward acquisition. We next characterize in greater detail the CA strategies participants relied on, specifically MFCA and MBCA.To assess whether subjects learnt the underlying vegetable/person reward probabilities, we calculated choice accuracy for each participant as the proportion of trials in which the person with the higher-expected generating-reward probability  was chosen. The mean accuracy across participants was 0.555, significantly above a 0.5 chance-level performance  preferentially (relative to choice-unrelated vegetables) change the By contrast, an MB system does not maintain and update values for the people directly. Instead, at choice, it calculates prospectively on-demand Another form of MBCA, which enacts our proposed importance hypothesis, does not treat all vegetables equally. For instance, in the trial illustrated in To summarize our predictions, a finding that rewards pertaining to choice-related vegetables reinforce the chosen person’s MF value to a larger extent than choice-unrelated rewards, would constitute evidence for CM guidance to MFCA. Likewise, evidence that rewards to vegetables that were important to choice reinforce MB values of these vegetables to a larger extent as compared to nonimportant vegetables would provide evidence of an “importance”-based modulation of MBCA.SI Appendix, Figs. S2–S4. A full description of these models is deferred to a later section.In examining signatures of relatedness and importance-based influences on MFCA and MBCA to people and vegetables respectively, we first present “model agnostic” analyses, which focus on trial transitions . These analyses are supported by validating simulations using computational models, reported in Anticipating our model-agnostic analysis results, we found that MFCA based on choice-related outcomes is stronger than for unrelated outcomes, supporting our hypothesis of CM guidance to MFCA. In the model-agnostic analyses, we considered only trials, n+1, which offered as a choice option of the person chosen on trial n  to the common vegetable exerts on choice repetition. These reward effects provide signatures for CA processes that had occurred at the feedback phase of trial n. To test a choice-relatedness hypothesis , we compared signatures of MFCA for an outcome that was either related to the trial-n choice or unrelated to that choice as follows.SI Appendix, Fig. S2 and S4A for validating simulations). To illustrate, on trial n+1 (t(1333) = 7.99, and P = 3 × 10⁻15) in support of a conclusion that on trial n, credit from a choice-related vegetable was assigned in an MF manner to the person.First, to assess MFCA for a trial-n choice-related outcome, we assessed the common outcome  effect. We showed previously  that a prial n+1 A, an MB rial n+1 B a main t(1333) = −1.77, and P = 0.078). Thus, there is no evidence that a trial-n choice-unrelated reward reinforces positively the MF values of the chosen person. Below, we revisit this issue further in the context of our computational models. To anticipate our results, we found that credit from a vegetable unrelated to choice is assigned significantly as a negative quantity to the chosen person .Second, to assess MFCA for a trial-n choice-unrelated outcome, we evaluated the effect of the Absent vegetable . Notably, a trial n reward (or lack thereof) for this vegetable will not affect MB calculations on trial n+1 . Hence, an absent reward can only exert an effect on choice via an MFCA pathway. Our logistic mixed-effects model revealed a negative absent-outcome trend  = 48.35 and P = 6 × 10−12), in support of our hypothesis. Indeed, in the absence of CM-based guidance, MFCA should be observed to an equal extent for all outcomes .To address our hypothesis that CM guides MFCA, we compared the effects of the common (related) and the absent (unrelated) outcomes B. CruciaPrior to testing our second hypothesis pertaining to importance-based MBCA, we show that MBCA occurs for both choice-related and -unrelated vegetables.F = 43.6, and P = 6 × 10−11; SI Appendix, Figs. S2 and S4B for validating simulations).To assess MBCA to a trial-n choice-related outcome, we compared the Unique and the Common reward effects on choice repetition. Note that both the common and unique vegetables are related to the trial n choice. However, unlike a common reward that fosters choice repetition via an MF pathway alone (for reasons explained above), a unique reward contributes to choice repetition via both the MF pathway  and the MB pathway . Our logistic mixed-effects model revealed that a choice-repetition effect of reward versus nonreward on trial n was stronger for the Unique than the Common vegetable  = 30.74, P = 4 × 10−8; SI Appendix, Figs. S2D and S4B for validating simulation). In sum, these results support a conclusion that MBCA occurs for both  choice-related and choice-unrelated outcomes. Additionally, the difference between these two contrast effects, for the related and unrelated outcomes, was nonsignificant  = 0.36, and P = 0.55), providing no support for the idea that the extent of MBCA to outcomes differs as a function of choice relatedness.Considering MBCA to trial-n choice-unrelated outcomes, we found the Other vegetable effect was more negative than an Absent vegetable effect  will increase to a greater extent after receiving a reward on trial n if garlic was “important” versus “unimportant” on that trial. This would then induce a stronger MB effect on choice repetition on trial n+1. Thus, our hypothesis predicts a positive interaction between the Unique outcome and importance on choice repetition and, for similar reasons, a negative Other outcome × importance interaction.t(1333) = 2.22, and P = 0.027). A simple effects analysis revealed that the Unique outcome effect was positive when it was “unimportant”  = 80.56, and P = 9 × 10−19) but even more so when it was “important”  = 162.51, and P = 3 × 10−35) on trial n. Similarly, we found a negative interaction effect between Importance and the Other outcome  = −3.85, and P = 1 × 10−4) such that the simple Other outcome effect was negative when it was “unimportant”  = 14.91, and P = 1 × 10−4) but more so when it was “important”  = 50.42, and P = 2 × 10−12) on trial n. These findings support the hypothesis that MBCA is enhanced for “important” versus “unimportant” outcomes . Note, the main effects for both Common and Absent outcomes reported earlier were not qualified by interactions with “Importance”  Unique and Other vegetables were “important” on trial n. We found B a positGiven the nature of learning, the strongest effects of outcomes on a trial are expected to be evident on the very next trial. In order to probe MFCA, we have so far concentrated our model-agnostic analyses on the half of the trial-to-trial transitions for which trial n+1 featured the trial n choice. However, no such restriction is necessary to probe MBCA since outcomes on trial n affect choices on trial n+1 even when the person chosen on trial n is not on offer. To address this limitation, we performed an additional analysis that provided a signature of enhanced MBCA for important outcomes, one based on all trial transitions C. By dest(134) = 7.93, and P = 4 × 10−14; Left: b = −0.52, t(134) = −9.67, and P = 2 × 10−19) and that critically, these effects were stronger when the two distinctive vegetables were important on the previous trial, as evident from the interactions between rewards and importance  = 2.15, and P = 0.032; Left: b = −0.16, t(134) = −2.35, and P = 0.02). Notably, whereas MFCA influences could account for the reward effects, influences of MBCA alone account for the interactions with importance . These findings converge with those reported in the previous section and again support our hypothesis that MBCA is enhanced for important outcomes.To test this prediction, we used a mixed-effects logistic model , allowing us to probe estimated CA parameters to test our hypotheses. Note, the Common and Exclusive parameters pertain to choice-related outcomes. Similarly, the Exclusive and Counterfactual parameters pertain to important outcomes as the values of these outcomes contribute to a contrast between MB values of the two offered persons during choice.We modeled choices as arising from a mixture of MB and MF contributions. In our full model, each outcome  To test the hypothesis of no MFCA contribution in our task, we formulated a “pure MB” submodel, which set all four MFCA parameters to 0; behaviorally, this model should not predict our model-agnostic signatures pertaining to MFCA. 2) Similarly, to test the hypothesis of no MBCA contribution to performance, a “pure MF” submodel was formulated, which set all four MBCA parameters to 0; behaviorally, this model should not predict our model-agnostic signatures pertaining to MBCA. 3) To test the hypothesis that MFCA may affect performance without guidance from a CM, we formulated a “no CM guidance for MFCA” submodel. This forced all four MFCA parameters to be equal; behaviorally, this model should not predict model-agnostic signatures in which there is enhanced MFCA for related as compared to unrelated outcomes. 4) To test the hypothesis that unrelated rewards do not affect MFCA, a “no MFCA for unrelated choice outcomes” submodel was formulated, which constrained the MFCA parameters for the choice-unrelated  outcomes to 0; behaviorally, this model should not predict a model-agnostic signature pertaining to negative MFCA for unrelated outcomes (note models 3 to 4 included the four MBCA parameters). 5) To test the hypothesis that MBCA is not modulated by outcome importance, we formulated an “egalitarian MBCA” submodel, which constrained all four MBCA parameters to be equal (note this model still had the four-parameter MFCA component); behaviorally, this model should not predict our model-agnostic signatures pertaining to importance-based modulation of MBCA.SI Appendix, Supplementary Methods). In brief, this method is based on classical statistical hypothesis testing, where for model comparisons, a sub model serves as the H0 null hypothesis and the full model as the alternative H1 hypothesis. We verified also that our model comparison method was suitably powered to reject each of the submodels at the group level . Below, we report for each model both the number of participants for which it was rejected , as well as a “group-level” test, for rejecting the null hypothesis that all participants rely on the submodel. Note rejecting the submodel at the group level supports an inference that a subset of participants rely on the submodel, but it does not imply the full model is more prevalent in the subject population .We compared each of these submodels in turn to our full model using a bootstrap generalized-likelihood ratio test , 27 .First, we rejected both the pure MB . SI Appendix, Supplementary Methods). Pooling together the various hybrid models, which include contributions from both MBCA and MFCA, revealed about 41% of the population is expected to rely on pure MFCA processing, another 27% rely on pure MBCA processing, and the remaining 32% is expected to exploit a form of Hybrid control  or “unimportant” (Common and Absent) for MB choice deliberations and whether it was related (Common and Exclusive) or unrelated  to the choice A. The foSI Appendix, Supplementary Methods). We found a positive main effect for choice “relatedness”  = 7.16, and P = 3 × 10−11). Neither the main effect for “importance”  = −0.41, and P = 0.686) nor the interaction between “importance” and “relatedness”  = 0.7, and P = 0.484) were significant  = 65.88, and P = 1 × 10−13), it was negative for choice-unrelated vegetables  = 8.43, and P = 0.004). Thus, not only do choice-unrelated outcomes not provide positive reinforcement, but they actually reinforce choices negatively.In our first analysis, we tested our hypothesis pertaining to CM guidance to MFCA, regressing, using a mixed-effects model, the four ML MFCA full-model parameters for each participant  on indicators specifying whether a parameter pertained to importance (I) and choice-relatedness (R) outcomes , used to test our hypothesis pertaining to importance modulation on MBCA, revealed a positive main effect for “importance”  = 2.48, and P = 0.014). Neither the main effect for choice “relatedness”  = 1.28, and P = 0.204) nor the interaction between “importance” and “relatedness”  = −0.65, and P = 0.519) were significant  = 25.04, and P = 1 × 10−6) and “unimportant”  = 9.38, and P = 0.003) outcomes. These results support our hypothesis that choice deliberations based on a CM bias MBCA. Indeed, while MBCA occurs for both important and unimportant outcomes, it is enhanced for the latter. Furthermore, when we calculated a separate importance-based modulation effect on MBCA for related (contrast: Exclusive − Common MBCA parameters) and unrelated outcomes , we found a positive correlation between the two . Thus, importance-based modulation of MBCA is coordinated across related and unrelated outcomes. Additionally, we verified that the interpretation of our two effects pertaining to outcome relatedness and importance are not confounded by parameter trade-offs , and we found no evidence that either MFCA or MBCA patterns were influenced by occasional transition-structure reminders .A similar mixed-effects model for the MB system . We found strong positive correlations  between the full model’s ML CA parameters and the corresponding BA parameters. Importantly, the mixed-effect models for the BA parameters supported the very same conclusions about CA in both systems .As explained above, to address participant heterogeneity we also ran our mixed-effects models (for MBCA and MFCA) for parameters that were estimated based on BA. For each participant, parameters were averaged across models with weights corresponding to posterior model probabilities  revealed a positive correlation between MBCA and choice sensitivity , which is expected because, as we show below, MBCA is an effective way to learn to make good choices. Additionally, we found a positive correlation between the overall level of MFCA and CM guidance to MFCA . Neither of these correlations survived a Bonferroni correction for multiple (10 in this case) hypotheses.We explored the relationships between five measures of CA. For each participant, we calculated four measures based on the ML full-model parameters: overall levels of MBCA , overall level of MFCA , CM guidance to MFCA (the contrast between average MFCA parameters for related and unrelated outcomes), and importance-based modulation of MBCA (the contrast between average MBCA parameters for important and unimportant outcomes). The fifth measure was our model-agnostic measure of choice sensitivity. Pairwise correlation between these measures . For each agent, we calculated a standardized measure of reward earnings defined as the excess earnings over a random guessing policy, relative to the excess earning of an omniscient “oracle agent” that is rewarded according to the expected reward of the better of the two bandits . We address MFCA and MBCA agents in turn .Our findings raise important questions regarding the effects of the reported modulations of CA (based on a CM) on the acquisition of reward. We therefore simulated agents performing our task under different regimes and over broad ranges of CA parameters  and for the ratio between unrelated  and related outcomes (y axis). First, as expected, in the absence of guidance from a CM (bottom row of panel), when CA for related and unrelated outcomes are equal, earnings match those of a random choice policy (standardized earnings are 0) because the MF system lacks reliable information to distinguish between the values of the different individuals. As the unrelated MFCA parameters decrease (moving upward in the panel) manifesting guidance from a CM, standardized earnings increase. Earnings are maximized when these parameters are negative and equal in magnitude to the related MFCA parameters. SI Appendix, Fig. S14 A and B) .To assess whether guidance from a CM is instrumental for MFCA, we simulated reward earnings for various regimes of MFCA. Next, we asked whether importance-based modulation fosters earnings. Following the same design as SI Appendix, Fig. S14 C and D). However, in the modified version of the task, an MFCA modulation based jointly on relatedness and importance boosts earnings .However, in each trial of our task, we present a random pair of individuals. Consequentially, current-state importance does not predict future-state importance. In more ecological environments, we might expect the importance of task aspects for decisions would enjoy positive temporal autocorrelation, such that currently important aspects are more likely also to be important for subsequent decisions. These are the very circumstances that importance-based modulation of MBCA should improve performance. Finally, we assess which of the two forms of CA is more instrumental for reward acquisition. In summary, we find that MB control outperforms MF control with respect to earnings. However, to the extent that one relies on MF control and guidance from a CM, manifesting in negative CA for unrelated outcomes is beneficial. Furthermore, whereas importance-based modulation of MBCA is inefficient in our task, it can be instrumental in environments characterized by the temporal consistency of important task states. We discuss these findings in greater detail below.We recently described a dual-outcome bandit task  that dis30We first show that a CM guides MFCA. This supports the notion that an MF system, which retrieves cached action values during choice without reference to task transition structure can, when assigning credit to past actions, be guided by a CM. Many previous experimental investigations simplified greatly the problem of associating actions with outcomes, for instance, by providing relevant rewards and/or state information immediately after each action. In such cases, MFCA can exploit factors such as temporal contiguity , renderiIn the context of our task, in the absence of CM guidance, MFCA must be equally affected by choice-related and -unrelated outcomes. In striking contrast to this, we found that action-related and -unrelated outcomes reinforced MF action values positively and negatively, respectively. In our computational treatment, CM-based guidance is achieved by modulating the extent of updates of MF values based on outcomes according to the outcome structure of actual choices. One could equally imagine the operation of an architecture such as DYNA , 34, in 35The negative choice-unrelated MFCA effect might reflect an MF attempt to learn relative rather than absolute action values . ConceivBy stark contrast with updates to MF values, MB values were affected almost equally by outcomes that were related, or unrelated, to choice. However, unlike MF values, MB updates were seemingly affected by the decision-making processes associated with a choice, with a greater effect seen for outcomes a CM could discriminate as being determinative  compared to those that were not (Common and Absent). We suggest this fits with the idea that MB deliberation differentially activates, or primes, components of a CM based on their “importance” and that such state activation facilitates CA. Hypothetically, other variables, such as the number of times a state was incorporated into previous action plans, could similarly contribute to a gradient of activation over a CM. Future studies should examine which variables affect state activation and how they affect the extent of CA. A rather different possibility is that “importance”-based MBCA is mediated by an attentional process whereby important outcomes capture more attention during outcome presentation. Again, it will be of interest to probe these attentional influences on MBCA, for example, by presenting outcomes in parallel rather than serially and measuring the level of attention allocation to different outcomes , 41.t(164) = 6.28, P = 3 × 10−9; Our findings raise subtle questions as to the benefits of the observed CM-based modulations of MBCA and MFCA. Using model simulations, we find a rich picture. First, to the extent that one relies on MFCA, guidance from a CM that manifests in negative CA for choice-unrelated outcome is instrumental for simulated earnings. Furthermore, we found that simulated earnings were maximal when MFCA for related and unrelated outcomes were equal in magnitude but reversed in sign. Empirically, however, the positivity of MFCA to related outcomes in our task was larger than the negativity of MFCA to unrelated outcome  which might influence this arbitration and the expression of individual difference in strategy selection.In sum, our results encourage a generalized view of model-based processing. That is, instead of focusing narrowly on the sort of prospective reasoning of the sort that underlies planning, it suggests a broader perspective on the types of operations supported by a CM, where these include retrospective inference of state uncertainty  and the https://uclpsychology.sona-systems.com/Default.aspx?ReturnUrl=/) with restrictions of having normal or corrected vision, being nondyslexic, being a UK-based student, and being born after 1981. The study was approved by the University College London Research Ethics Committee (Project ID 9929/002). Subjects gave written informed consent before the experiment.A total of 44 participants were recruited from the SONA subject pool .After learning, participants played eight practice-bandit trials to verify that they understood the task. These practice trials proceeded as described below with the sole difference that no time limit was imposed on a choice. They next played seven blocks, each comprising 56 bandit trials. On each trial, a pair from the four persons were offered for choice, and participants had 750 ms to choose one of these objects (left or right mouse click). Offered persons always shared one vegetable in common. This defined four person pairs, each presented on 14 trials (per block) in a random order. Following a choice, participants saw sequentially, and in random order, whether each of the four vegetables that the chosen person grows was sold or not. Participants earned a notational £1 per sale of each of the two vegetables that were grown by the person they chose (they earned no money for the two nonrewarded vegetables). Importantly, the feedback stage indicated to participants neither which pair of vegetables were grown by their chosen person nor their earning on that trial. The sale probabilities (“demands”) of the four vegetables evolved across trials according to four independent Gaussian-increment random walks with reflecting boundaries at After each block was completed, participants had a forced 1-min (minimum) break. After the break, participants were informed that all vegetable reward probabilities were reset to new values, and, therefore, they should form new impressions of these when the task resumes. Additionally, at the beginning of blocks 1 and 4, participants received refresher training on the transition structure.The task lasted about 60 min. Participants were paid £8 per hour plus a performance-based bonus, which was calculated based on the total amount of earned rewards on three randomly sampled trials.Two participants were excluded from data analyses due to disengagement with the task. One participant used the same response key for 98% of the trials, and the other switched the response key on 86% of trials. The remaining 42 participants were the targets for the analysis.Our model-agnostic analyses were conducted using logistic mixed-effect models (implemented with MATLAB’s function “fitglme”) with participants serving as random effects with a free covariance matrix. In our first analysis, we used only trials n+1 that offered for choice the trial n–chosen person. Our regressors COMMON (Common vegetable), UNIQUE (Unique vegetable), ABSENT (Absent vegetable), and OTHER (Other vegetable) coded whether trial n outcomes were rewarding (coded as +0.5 for reward and −0.5 for nonreward); the regressor IMPORTANCE coded whether the UNIQUE and OTHER outcomes were important on the previous trial n (+0.5 for important and −0.5 for unimportant); and the regressed variable REPEAT indicated whether the choice on the focal trial n+1 was repeated. PART coded the participant contributing each trial. The model, in Wilkinson notation, was REPEAT ∼ IMPORTANCE × (COMMON + UNIQUE + ABSENT + OTHER) + (IMPORTANCE × (COMMON + UNIQUE + ABSENT + OTHER)|PART). We used an F-test to examine contrasts on fixed effects.We performed an additional analysis relying on all trial-to-trial transitions. On each trial (n+1), the two offered persons shared one vegetable in common, and each had one unique vegetable. The regress variable CHOOSE_RIGHT indicated whether the person offered on the right side of the display was chosen , and our regressors were R1 and R2, coding whether the unique vegetables of the right-side and left-side persons were rewarded on the previous trial n (coded as +/−0.5), and IMPORTANCE, coding whether these two vegetables were important on trial n (coded as ±0.5). PART coded the participant contributing each trial. The model, in Wilkinson notation, was CHOOSE_RIGHT ∼ IMPORTANCE × (R1 + R2) + (IMPORTANCE × (R1 + R2)|PART). We used an F-test to examine whether any of the fixed-effects interactions with importance were significant. If this F-test was significant, we proceeded to examine the significance of the individual interaction terms . Similarly, we used F-tests to examine whether any of the reward effects were significant. If the F-test was significant, we examined the significance of the individual terms .We formulated a hybrid RL model to account for the series of choices for each participant. In the model, choices are contributed by both the MB and MF systems. The MF system caches a where the “c”s are four free MFCA parameters corresponding to the four outcome types, the “r”s are the rewards for the four outcome types (codes as 1 for reward or −1 for nonreward), and Unlike MF, the MB system maintains Following a choice, the MB system updates the where Our model additionally included progressive perseveration for chosen persons. After each trial, the perseveration values of each of the four persons updated according towhere During choice, a net Q value was calculated for each offered person:The Supplementary File


Hstx2 on Chr X and Hst1 on Chr 17 by murine forward genetic approaches. HS gene on Hst1 was reported to be Prdm9. Intersubspecific polymorphisms of Prdm9 induce HS in hybrids, and Prdm9 null mutation leads to sterility in the inbred strain. However, HS gene on Hstx2 remains unknown. Here, using knock-out studies, we showed that HS candidate genes on Hstx2 are not individually essential for spermatogenesis in B6 strain. We examined 12 genes on Hstx2: Ctag2, 4930447F04Rik, Mir743, Mir465d, Mir465c-2, Mir465b-1, Mir465c-1, Mir465, Gm1140, Gm14692, 4933436I01Rik, and Gm6812. These genes were expressed in adult testes, and showed intersubspecific polymorphisms on expressed regions. This first reverse genetic approach to identify HS gene on Hstx2 suggested that the loss of function of any one HS candidate gene does not cause complete sterility, unlike Prdm9. Thus, the mechanism(s) of HS by the HS gene on Hstx2 might be different from that of Prdm9.F1 hybrid progenies between related subspecies often show hybrid sterility (HS) or inviability. HS is caused by failure of meiotic chromosome synapsis and sex body formation in house mouse. Previous studies identified two HS critical genomic regions named  This HS is the barrier distinguishing related species by disturbing the gametogenesis in the hybrid. HS is widely observed around intersubspecific hybrids such as yeast, plants, insects, birds, and mammals4. In 1922, Haldane’s rule was reported as the observation that if only one sex of the hybrid is inviable or sterile, that sex is the heterogametic sex (XY or ZW)5. Additionally more than 80 years ago, Dobzhansky, T. (1937) and Muller, H. (1942) proposed a two-locus model called Dobzhansky-Muller incompatibility (hereafter DMI) hypothesis that postzygotic isolation arises from a negative epistatic interaction between incompatible alleles that evolved on two independent evolutionary lineages7. Previous studies showed a large effect of Chr X (Chr Z) on reproductive isolation, particularly on HS or hybrid inviability11. In the last 30 years, several HS genes and hybrid inviability genes were identified in budding yeast, thale cress, fruit fly, and house mouse25. In Drosophila, HS genes: OdsH and Ovd, and hybrid inviability gene: Hmr and locate on Chr X21. However in house mice, these orthologous genes have not reported. Although several researchers proposed to explain this heterogametic HS or inviability as being controlled by Chr X (Chr Z) in vertebrata28, the X-linked (Z-linked) causative gene for Haldane’s rule and DMI has remained unclear for over a century.Postzygotic reproductive isolation between related subspecies often results in hybrid incompatibility such as hybrid sterility (HS) or inviabilityHst1 and Hstx2, were found by murine forward genetics32. The first HS locus in mice, Hst1 was identified as a polymorphic variant on Chr 17 between two laboratory strains, C57BL10/Sn and C6H/Di, both predominantly of Mus musculus domesticus (hereafter Mmd) origin29. To identify HS gene on Hst1, Forejt, J. et al. established HS murine recombinant inbred model using PWD/Ph (hereafter PWD) inbred strain derived from Mus musculus musculus (hereafter Mmm) subspecies and C57BL/6 (hereafter B6) inbred strain derived from Mmd subspecies34. PWD was established from a single pair of wild mice of the Mmm subspecies caught in 1972 in Central Bohemia, Czech Republic35. Both subspecies diverged from a common ancestor approximately 0.3 to 0.5 million years ago36. This model shows asymmetric HS, wherein (PWD × B6) F1 hybrid  shows sterility, while (B6 × PWD) F1 hybrid  shows semi-fertility36. To identify these HS loci, Gregorová, S. et al. also established intersubspecific chromosome substitution (consomic) strains C57BL/6-Chr#PWD/Ph/ForeJ carrying individual Mmm chromosomes or their parts on Mmd background37. The HS gene on Hst1 was identified by the forward genetic approach as PR domain containing 9 (Prdm9)24, and later was shown to control meiotic recombination hotspots39. Prdm9 encodes for histone H3 lysine 4 trimethyltransferase that controls the hotspots of DNA double strand breaks (DSBs) at meiotic prophase in spermatocytes. Hstx2 was found out by consomic strains C57BL/6-Chr XPWD/Ph/ForeJ carrying Mmm Chr X or their parts on Mmd background32. The 4.7 Mb  HS critical region on Chr X, Hstx2, was identified by quantitative trait locus (QTL) analysis of male fertility phenotypes in these consomic strains32. They revealed that HS is also controlled by Hstx2 of PWD32.The two HS loci, Prdm9 on Hst1, the HS gene on Hstx2 remains unknown. Identifying the molecular mechanism of HS controlled by Chr X can unravel the molecular mechanism of Haldane’s rule in vertebrata. Forward genetic approaches have a limit to narrow down to only 4.7 Mb Hstx2 critical region, because Hstx2 may lie on a recombination cold spot41. Hence, reverse genetic approach is required to identify the HS gene on Hstx2.Unlike the HS gene Prdm9 heterozygosity (Prdm9B6/PWD), autosomal heterozygosity and the PWD allele of Hstx2 (Hstx2PWD)42. One of HS mechanism model was explained by hybrid incompatibility between Prdm9B6/PWD and autosomal heterozygosity without DMI at least in house mouse43. Minisatellite structure of the zinc finger array coding on DNA binding sites of PRDM9 has interspecific polymorphisms between B6 and PWD44. The binding sites were evolutionally eroded by DNA double-strand breaks determined by PRDM9 in each strain44. The affinity of PRDM9B6 to B6 autosomes and the affinity of PRDM9PWD to PWD autosomes decreases with evolution, respectively44. This is because the evolutionary erosion of genomic DNA occurs independently in each mouse sub-strain. In hybrid, PRDM9B6-determined hotspots occur mostly on the PWD chromosome and vice versa44. The major meiotic consequences of asymmetric DSB hotspots result in unrepaired DNA DSBs, meiotic asynapsis and abnormal sex body formation, leading to disruption of sperm formation43. Nevertheless, only this model cannot explain the asymmetric HS because this meiotic arrest is also controlled by Hstx2. Hstx2PWD is responsible for full sterility of (PWD × B6) F1 hybrid, while the B6 allele of Hstx2 (Hstx2B6) attenuates fertility of (B6 × PWD) F1 hybrid32. However, how Hstx2 regulates HS remains elusive. Therefore, we proposed three hypotheses of the role of Hstx2. First hypothesis is that the spermatogenic function of HS gene(s) on Hstx2 is lost in (PWD × B6) F1 male but partially remains in (B6 × PWD) F1 male. Second hypothesis is that dominant-negative Hstx2PWD impedes the spermatogenesis in hybrids. Third hypothesis is that Hstx2B6 rescues fertility of hybrids. Here, to verify whether Hstx2 are essential for spermatogenesis in the first hypothesis, we aimed to delete HS gene on Hstx2 in B6 mice. We hypothesised that HS gene on Hstx2 may have similar features to Prdm9, such as expressing in adult testes45, having intersubspecific polymorphisms on expressed region between Mmm and Mmd44, explaining HS mechanism by single locus43 and inducing sterility by knock-out (KO) in B6 genetic background46. If our first hypothesis is correct, the HS gene on Hstx2 KO B6 mice would be sterile. Therefore, we aimed to identify HS gene on Hstx2 through KO study.In a mouse model of intersubspecific hybrids between B6 and PWD, HS needs three factors, Hstx2 in adult B6 testes using databases. Next, we analysed intersubspecific polymorphisms on expressed regions between B6 and PWD, also PWK/Phj  by past reports and public database.To identify HS candidate gene, we investigated the expression of 32 genes on Hstx2 32, which carries 10 protein-coding genes and 22 microRNA (miRNA) genes , BioGPS (http://biogps.org/circadian/#goto=welcome) and miRbase (http://www.mirbase.org/), which revealed that of the 32 genes, 9 protein-coding genes: Ctag2, 4930447F04Rik, Gm1140, Gm14692, 4933436I01Rik, Fmr1, Fmr1nb, Gm6812, and Aff2, and all 22 miRNA genes were expressed in adult B6 testes  of HS candidate genes among B6, PWD, and PWK32  and we aligned PWK and B6 reference genome (GRCm38). A very recent study reported that Gm1140, Gm14692, and Gm6812 have intersubspecific missense SNPs between B6 and PWD, and Mir465 cluster shows copy number polymorphism between B6 and PWD (and PWK)40. Therefore, we added these genes to the targets.Male sterility of reciprocal hybrids between PWD and B6 is controlled by es Table . The onlWK Table . The nexCtag2, 4930447F04Rik, Gm1140, Gm14692, 4933436I01Rik, and Gm6812, and six miRNA genes, namely Mir743, Mir465d, Mir465c-2, Mir465b-1, Mir465c-1, and Mir465.Taken together, we targeted 12 HS candidate genes, composed of six protein-coding genes, namely Mir465d, Mir465c-2, Mir465b-1, Mir465c-1, and Mir465 are located on Mir465 cluster, which is composed of 6 repeats , and then each KO F0 founder were selected for KO allele, removing all genomic region of target gene. To confirm the CRISPR/Cas9 mutations, we performed genotyping using genomic PCR from mouse tail and then confirmed the KO allele. Thus, we generated each of the eight gene/cluster KO male founders  sites, one upstream of the target gene and the other downstream of it on B6 genetic background in order to remove all genomic region. ats Fig. ; as we c4933496I01Rik KO male founder generated wild-type female, suggesting that the founder was mosaicism. Except for the above, all other F1 female mice that were born from mating F0 male founders with female B6, showed the KO allele. Therefore, in our experiment, the male founders would not have shown mosaicism. These results suggested that the fertilisable sperm could have developed from the germ cell carrying the KO allele. Therefore, all eight KO male genotypes, 1 HS candidate gene/cluster per each, were fertile.To investigate fertility of each candidate gene KO male founder, the sexually mature KO male F0 founder was mated with sexually mature B6 wild-type female. F0 founder have the possibility of mosaicism; therefore, these KO F0 male founder may not show full knock out of the gene in the testes. If KO allele was inherited to next generation, it would imply that the germ cell carried the KO allele and could be developed to fertilisable sperm. From mating test, each heterozygote KO female mice was born Table . One of To investigate the spermatogenesis of each KO mice, histochemical analysis was performed. Peanut agglutinin (PNA) lectin histochemistry (LHC) is available as a marker of sperm. Immunohistochemistry (IHC) of phosphorylated form of the histone variant H2AX (γH2AX) is a marker of sex body on pachytene spermatocyte. IHC and PNA-LHC of testis section of each KO F0 founder showed sperm and sex body formation on these spermatocytes  of Hstx2 critical region on PWD Chr X, because there may be recombination cold spot on Hstx241. Recently, Lustyk, D. et al. reduced 4.7 Mb region of Hstx2 to 2.7 Mb (Chr X:66.51 Mb-69.21 Mb) by backcross where SPO11-driven Cas9 nuclease was targeted by CRISPR to Hstx2 interval in female meiotic prophase40. Nevertheless, this approach could not identify HS gene on Hstx2. Therefore, a reverse genetic approach is required to identify HS gene on Hstx2.Previous studies identified two HS loci by forward genetic approaches using consomic strainsPrdm9 is the only identified HS gene and is responsible for sterility phenotypes in male hybrids of house mouse52. Intersubspecific polymorphisms on the minisatellite cording for zinc-finger array of Prdm9, such as repeat variants and missense SNPs, and autosomal heterozygosity induce asymmetric DNA DSBs that cause sterility in hybrids44. Additionally, Prdm9 is expressed in adult testes and its null mutation leads to sterility in the inbred strain46. Therefore, we hypothesised that HS gene on Hstx2 may have similar features to Prdm9: intersubspecific polymorphisms of HS gene on Hstx2 might cause HS, and the HS gene null mutation may lead to sterility on B6 background, as in the case of Prdm9. However, some hybrid with a sufficiently high recombination rate did not show sterility by Prdm9 null mutation46, so that Prdm9 is not essential for meiosis in male mice of every species. At least in inbred male, Prdm9 is essential for spermatogenesis. In this study, we disregarded intersubspecific polymorphisms on intergenic and intron region. Therefore, another gene on Hstx2 which has other polymorphisms such as SNPs on its regulatory region might be HS gene. Additionally, we added 4 genes/cluster: Gm1140, Gm14692, Gm6812, and Mir465 cluster to the targets because these genes have intersubspecific missense SNPs between B6 and PWK. A very recent study reported that Gm1140, Gm14692 and Gm6812 have intersubspecific missense SNPs between B6 and PWD, and Mir465 cluster have copy number polymorphism between B6 and PWD40. Therefore, this report supports our selecting.Hstx2 was found to be essential for spermatogenesis on B6 genetic background. In our introduction, we proposed three hypotheses for the role of Hstx2. Based on our findings, we could partially exclude our first hypothesis, which was that the spermatogenic function of HS gene(s) on Hstx2 is lost in (PWD × B6) F1 male, but partially remains in (B6 × PWD) F1 male. However, in this hypothesis, the polygenic effect is retained. On Hstx2, there are a few related and adjacent genes. The coding sequence of Gm6812 is similar to that of 1700020N15Rik, which is located nearby Hstx2 (Chr X:69.9 Mb). The coding sequence of Gm6812 has only one missense SNP compared with that of 1700020N15Rik in both B6 and PWD mice. The coding sequence of Gm1140 is also same as that of Gm14692. These genes might complement each other functionally. Besides these possibilities, recent study reported that KO of several genes on Hstx2 resulted in arrested spermatogenesis in B6 mice53. The deletion of each Mir741, Mir871, and Mir880 did not affect spermatogenesis, but deletion of 6 miRNAs, Mir741, Mir463, Mir880, Mir878, and Mir871 disrupted spermatogenesis in B6 mice. Therefore, Mir463 or Mir878 might be essential for spermatogenesis, or polygene of these 6 miRNAs may have a critical role in spermatogenesis. The second hypothesis was that dominant-negative Hstx2PWD impedes the spermatogenesis in hybrids. Nineteen miRNAs on Hstx2 BAC transgenic mice carrying these autosomal genes show sterility54. Normally, these miRNAs are actively transcribed in spermatogonia and suppressed by meiotic sex chromosome inactivation in pachytene spermatocytes. In this BAC transgenic mice, these miRNAs are mis-expressed on pachytene, which induces spermatogenic defects in the BAC transgenic mice. Among the 19 miRNA genes, Mir743 and the Mir465 cluster showed intersubspecific polymorphisms between B6 and PWD. In our study, we generated Mir743 single gene KO B6 mice and Mir465 cluster KO B6 mice, which did not show male sterility. If the second hypothesis was correct, HS gene KO on Hstx2 of PWD in (PWD × B6) F1 male would not show sterility. The third hypothesis was that Hstx2B6 rescues fertility of hybrids, while Hstx2PWD cannot rescue HS. (PWD × B6) F1 show sterility caused by asymmetric DSBs43. Although the amount of asymmetric DSB in (B6 × PWD) F1 male spermatocyte is equivalent to that in (PWD × B6) F1 male, (B6 × PWD) F1 male shows semi-fertility43. This result suggests that HS in (B6 × PWD) F1 male is rescued without recovering the asymmetry of meiotic DSBs. Therefore, we propose another recovery mechanism of HS without repairing asymmetry of meiotic DSBs. We suspect that HS gene of PWD on Hstx2 cannot rescue HS in (PWD × B6) F1 male, while HS gene of B6 on Hstx2 can rescue HS in (B6 × PWD) F1 male, inducing asymmetric HS. If the third hypothesis was correct, HS gene KO on Hstx2 of B6 in (B6 × PWD) F1 male would not show sterility.However, in our study, none of the HS candidate genes on Hstx2 by reverse genetics, which revealed that Ctag2, 4930447F04Rik, Mir743, Mir465 cluster, Gm1140, Gm14692, 4933436I01Rik, and Gm6812 are not individually necessary for spermatogenesis in B6 mice. This result partially proved that the loss of function of one gene/cluster on Hstx2 does not cause complete HS. Furthermore, the HS gene on Hstx2 might cause HS by different mechanisms than that shown by Prdm9. Thus, our study contributes toward determination of the HS gene on Hstx2 by at least excluding out one possibility.In conclusion, we used a new approach to determine HS gene on C57BL/6 J (B6) and Jcl:CD1 (ICR) inbred strain were purchased from Charles River Laboratories  and CLEA Japan . All mice were housed in plastic cages under pathogen-free conditions in a room maintained at 23.5 °C ± 2.5 °C and 52.5% ± 12.5% relative humidity under a 14-h light:10-h dark cycle. Mice had free access to commercial chow  and filtered water. Animal experiments were carried out in a humane manner with approval from the Institutional Animal Experiment Committee of the University of Tsukuba in accordance with the Regulations for Animal Experiments of the University of Tsukuba and Fundamental Guidelines for Proper Conduct of Animal Experiments and Related Activities in Academic Research Institutions under the jurisdiction of the Ministry of Education, Culture, Sports, Science, and Technology of Japan.All mice were sacrificed over 10-week-old. After intraperitoneal (i.p.) injection of a fatal dose of pentobarbital, mice were transcardially perfused with phosphate-buffered saline (PBS) under anaesthesia. Testes, from which tunica albuginea were removed, were fixed overnight in 10%-Formaldehyde Neutral Buffer Solution  and then dehydrated in 70% ethanol at room temperature over 1 week. The fixed testes were embedded in paraffin and stored at room temperature until use. The testes were sectioned at a thickness of 6 µm, deparaffinised, immersed in 0.25% Triton X-100 in PBS and then the antigens were activated in Target Retrieval Solution  for 10 min at 121 °C. After blocking the sections by the blocking solution  for 60 min at room temperature, the sections were incubated with mouse IgG anti-γH2AX antibody  overnight at 4 °C in a chamber with high humidity. After washing the sections twice using PBS, goat anti-mouse IgG Alexa Fluor 647  and PNA lectin  were applied on the sections and incubated for 60 min at room temperature in a dark chamber with high humidity. The sections were washed twice with PBS and incubated with 4’,6-diamidino-2-phenylindole (DAPI) in PBS (1:500) for 10 min. After washing the sections using PBS, the sections were mounted with Prolong Gold antifade reagent with DAPI (Invitrogen). Images of seminiferous tubules were captured using a fluorescence microscope CCD camera  and processed using BZ-X analyzer software (KEYENCE).Genomic DNA was extracted from the tails of 3-week-old mice. Genotyping PCR was performed using PrimeSTAR GXL DNA Polymerase  or AmpliTaq Gold DNA Polymerase (Applied Biosystems); the primers used for this are listed in Table 55. Female B6 mice were i.p. injected with pregnant mare serum gonadotropin (PMSG) and human chorionic gonadotropin (hCG) with a 48-h interval, and mated with male B6 mice. The zygotes were collected from oviducts. Then, two pX330 , targeting two CRISPR sites of each HS candidate gene, was injected into the pronuclei according to standard protocols. The injected embryos (pronuclei stage) were then transferred into pseudopregnant ICR females. The electroporation was performed as reported previously, with some modification56. The sgRNA was synthesised and purified using the GeneArt Precision gRNA Synthesis Kit  and dissolved in Opti-MEM (Thermo Fisher Scientific). PMSG and hCG were i.p. injected into female B6 mice with 48-h interval, and unfertilised oocytes were collected from their oviducts. We then performed in vitro fertilisation with these oocytes and sperm from B6 mice according to standard protocols. Five hours later, two sgRNA (25 ng/µl each) targeting two CRISPR sites of each HS candidate gene, and GeneArt Platinum Cas9 Nuclease  were electroporated into these zygotes using the NEPA 21 electroporator . The poring pulse was set to: 225 V, 2 ms pulse width, 50 ms pulse interval, and + 4 pulse number. The transfer pulse was set to: 20 V, 50 ms pulse width, 50 ms pulse interval, and ± 5 pulse number (attenuation rate was set to 40%). After electroporation, the developed 2-cell embryos were transferred into the oviducts of pseudopregnant ICR females.To remove all genomic region of each HS candidate gene, we respectively designed two sgRNAs, one whose target site was upstream of the target gene and the other was downstream of it on B6 genetic background. The sequences of the sgRNAs are listed in Table Supplementary information.


Compared with physicochemical methods, the microbial degradation of acephate and methamidophos is emerging as an eco-friendly method that can be used for large-scale treatment. In recent years, microorganisms capable of degrading methamidophos or acephate have been isolated, including Hyphomicrobium sp., Penicillium oxalicum, Luteibacter jiangsuensis, Pseudomonas aeruginosa, and Bacillus subtilis. Enzymes related to acephate and/or methamidophos biodegradation include phosphotriesterase, paraoxonase 1, and carboxylesterase. Furthermore, several genes encoding organophosphorus degrading enzymes have been identified, such as opd, mpd, and ophc2. However, few reviews have focused on the biochemical pathways and molecular mechanisms of acephate and methamidophos. In this review, the mechanisms and degradation pathways of acephate and methamidophos are summarized in order to provide a new way of thinking for the study of the degradation of acephate and methamidophos.Acephate is an organophosphate pesticide that has been widely used to control insect pests in agricultural fields for decades. However, its use has been partially restricted in many countries due to its toxic intermediate product methamidophos. Long term exposure to acephate and methamidophos in non-target organisms results in severe poisonous effects, which has raised public concern and demand for the removal of these pollutants from the environment. In this paper, the toxicological effects of acephate and/or methamidophos on aquatic and land animals, including humans are reviewed, as these effects promote the necessity of removing acephate from the environment. Physicochemical degradation mechanisms of acephate and/or methamidophos are explored and explained, such as photo-Fenton, ultraviolet/titanium dioxide (UV/TiO Organophosphate compounds (OPs) are one of the most widely used pesticides because of their broad spectrum, specificity, and high efficiency toward insects and pests . AcephatO, S-dimethyl-acetyl-phosphoramidothioate, molecular weight (MW) = 183.17]  (Methamidophos ( 141.12)  is also  141.12) . Methami 141.12) . It exer 141.12) . In addi 141.12) . Because 141.12) .Acephate and methamidophos are used in enormous quantities because of their high efficiency in agriculture and other industrial purposes, which leads them to remain in various environments for many years . Acephat2, ultrasonic ozonation, and ionizing irradiation, etc. are widely studied for acephate or methamidophos  the toxicity of acephate and methamidophos, and their removal; (II) the different oxidation or reduction methods of physicochemical degradation; (III) the different types of natural degradation strains, or genetically engineered microorganisms; (IV) the organophosphorus degrading enzymes and their encoding genes.The extensive use and long term exposure to acephate and methamidophos results in the cumulative effect of these compounds release into the environment, which consequently results in the direct or indirect poisoning of non-target organisms. We summarize the toxic effects of acephate and methamidophos on aquatic and land animals, including humans in Zebrafish is a commonly used model test organism due to its advantages of high genetic and organ system homology to humans, external fertilization, high fecundity, and transparency in early adulthood . It has Drosophila is also a model test organism that has amazing similarities in gene structure and function with higher vertebrates. Acephate contamination at higher concentrations than 5 g/mL can cause DNA damage and mortality in the fruit fly, and it may disrupt the balance of oxidase and antioxidant enzymes, such as catalase (CAT), glutathione-S-transferase (GST), cytochrome P450 (CYP450), AChE, and superoxide dismutase (SOD) (se (SOD) . Chronicse (SOD) . Earthwose (SOD) . Acephatse (SOD) . Methamise (SOD) .Overuse of acephate and methamidophos can lead to an increase in high blood sugar, impaired metabolism, DNA damage, reproductive barriers, and cancer in rats . AcephatThe human body can be very vulnerable when exposed to methamidophos or acephate. Acephate could be a genotoxin, which would make it a severe threat to human health. It can cause chromosomal changes and DNA damage in human lymphocytes . Moreove2, and ultrasonic ozonation  are a more efficient composite technology that combines the advantages of different physicochemical degradation methods to more efficiently remove methamidophos and acephate; examples of these methods include photo-Fenton process, UV/TiOzonation .3O4/McM-41 can completely remove acephate in 40 min (50 mg/L) or 60 min (100 mg/L)  (2400 g.a.i./h) for 20 h  . Under tectively . TiO2 isiciently . Furthersticides . The phofor 20 h . TiO2 isO-methl-N-acetylphosphoramidate and the more toxic methamidophos  . Reducinls (•OH) . Negativ2 has been studied. Under UV irradiation, nano TiO2 catalyzed 95% degradation of methamidophos within 4 h  and the pseudofirst-order rate constants are lnC = −0.757t + 5.9, R2 = 0.9776; 0.916 min and 0.757/min, respectively  can catalyze the degradation of acephate, but they cannot catalyze the degradation of methamidophos . In contthin 4 h . In anot studies . It was s 12 g/L . It was ectively . Even inmidophos . Electromidophos . Adsorpt2 is shown in P-formylphosphonamiddothioate and phosphine carboxylic acid, respectively. When the P-N bond of methamidophos is broken, an O, S-dimethyl phosphonothioate dimer is generated, which is more prone to further degradation. The intermediate products 1-aminoethanol and trimethoxymethane form the products acetamide and dimethoxymethanol, respectively, resulting in complete mineralization. Phosphoric acid is the main final product.The possible photodegradation pathways of methamidophos catalyzed by TiOThere is growing interest in microbiological degradation technologies because of the risk to life of pesticide residues, which provide cheap and efficient acephate and methamidophos detoxification to complement expensive chemical methods. Microbial degradation is a potential way to decontaminate pesticide-contaminated sites . BiodegrO-methyl-N-acetylphosphoramidate. Pseudomonas sp. Ind01 was able to degrade acephate by promoting the first step of acephate mineralization but could not utilize the methamidophos, which is involved in the process of O-methyl-N-acetylphosphoramidate  in 7 days. This strain not only degrades acephate but is also able to efficiently degrade other pesticides like dimethoate, parathion, methyl parathion, chlorpyrifos, and malathion. Thus, P. aeruginosa strain Is-6 shows high degradation ability in contaminated soil, indicating its potential in environmental remediation  encoding plasmid was immobilized at a low temperature in polyvinyl alcohol (PVA) cryogel to form a biocatalyst with high activity, stability, and mechanical strength , and eventually phosphoric acid is generated. In the process of biodegradation, PTE plays a primary role in catalyzing the first step of acephate degradation. The breaking of the P-S and P-O bonds of acephate and its intermediates is mainly dependent on the hydrolysis of PTE  , which can not only use glucose, fructose, ethanol, and gal as carbon sources and energy but can also degrade various organophosphorus  . Penicil sources . Acinetoosphorus . Isolaten source . The intn source . Interess MA-B12 . In part-S bonds . Few micO, S-dimethyl hydrogen thiophosphate generate phosphoric acid, methyl mercaptan, and methanol with the breaking of P-O and P-S bonds. In particular, methyl mercaptan in methamidophos degradation bacteria generates further dimethyl sulfide and dimethyl disulfide, which are not found in the acephate biodegradation pathway.As shown in Acephate and methamidophos are highly toxic organophosphate pesticides for long term use, and their microbial degradation (including molecular and genetic mechanism) has attracted extensive attention due to its ecofriendly effectiveness . In addip)-isomers of acephate and methamidophos  is an effective tool to degrade organophosphorus pesticides. PTE has the stereoselectivity to degrade organophosphorus pesticides and tends to degrade (Smidophos . Most ste of 9.0 . Anothers source . PTE isoer bonds . Phospho ability .Schizaphis graminum (Rondani), is tolerant to organophosphate pesticides, and it can significantly improve the resistance ability of Schizaphis graminum (Vulcanisaeta moutnovskia (VmutPLL)  is 1098 bp long, encodes a protein with 366 amino acid residues, and has a molecular weight of 40 kDa. The enzyme has great potential in cleaning up contaminated pesticides  . A Phe36toxicity . Cattle sticides . Rumen esticides . EnzymesEnzymes that are fixed can generally be used to improve efficiency. In the presence of appropriate immobilization, the degradation effect of the degrading enzyme is slightly better than that of the free enzyme, with a higher reuse rate and easier preservation . After aopd, mpd, and ophc2.Biodegradability is determined by genes, and genetic engineering technology may be used to carry out gene recombination and to enhance biodegradability. Therefore, it is very important to extract resistance genes. To date, many genes encoding organophosphorus degrading enzymes have been found, which will be of great support for the promotion of organophosphorus biodegradation, such as opd is a widely studied gene. The opdE gene has been isolated from Enterobacter sp. cons002, which has a wide range of degrading activities against organophosphorus pesticides  were isolated from Bemisia tabaci, in which coe1 was overexpressed (about 4-fold) in the organophosphate-resistant strain. Sufficient data and biochemical evidence support that increased coe1 and coe2 activity is involved in Bemisia tabaci resistance to organophosphate insecticides   . Under pfornica) . Carboxyplituter . In the Laodelphax striatellus to obtain insect cross-resistance to acephate, deltamethrin, imidacloprid, methomyl, carbosulfan, and diazinon   . Earthwolla (CP) . The emein situ repair of methamidophos and methamidophos. Therefore, in order to understand the genetic analysis of acephate and its related catabolic genes, we need to use advanced molecular technologies such as metagenomics, proteomics, and transcriptome analysis to reveal the missing links and evolutionary mechanism and metabolic pathway involved in the process of bio-degradation. In the future, metagenomics will serve as a useful tool to predict microbial degradation in polluted habitats and may facilitate the practical application of acephate and methamidophos degrading microorganisms from various contaminated sites.In modern agricultural production, acephate and methamidophos play important roles in controlling pests and increasing the crop yield. However, improper use of acephate and methamidophos can lead to critical environmental pollution and life-threatening health problems due to the high toxicity of methamidophos to non-target organisms. Many physicochemical methods have been developed and applied for the remediation of acephate and methamidophos, but they are thought to be too expensive to use on a large scale. Therefore, microbial degradation is considered to be a better and effective degradation method for acephate and methamidophos. Microorganisms capable of metabolizing acephate and methamidophos have been isolated, but further studies are needed, such as the continued development and utilization of degrading enzymes, the development of engineered degrading microorganisms, and overcoming environmental complexity. Microbial degradation kinetics, degradation pathways, and related enzymes and functional genes need to be further studied, as this is conducive to the SC conceived of the presented idea. ZL contributed to the writing and prepared the figures and tables. SP, WZ, SM, PB, and SC participated in revising the manuscript. All the authors approved it for publication.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.


In general, CCAAT-binding transcription factors form heterodimers or heterotrimeric complexes that bind to CCAAT sequences within the promoters of target genes and regulate various cellular processes. To date, except Hap complex, CCAAT-binding complex has been rarely reported in fungi. In this study, we characterized two CCAAT-binding transcription factors (Fct1 and Fct2) in the plant pathogenic fungus Fusarium graminearum. Previously, FCT1 and FCT2 were shown to be related to DNA damage response among eight CCAAT-binding transcription factors in F. graminearum. We demonstrate that the nuclear CCAAT-binding complex of F. graminearum has important functions in various fungal developmental processes, not just DNA damage response but virulence and mycotoxin production. Moreover, the results of biochemical and genetic analyses revealed that Fct1 and Fct2 may form a complex and play distinct roles among the eight CCAAT-binding transcription factors encoded by F. graminearum. To the best of our knowledge, the results of this study represent a substantial advancement in our understanding of the molecular mechanisms underlying the functions of CCAAT-binding factors in eukaryotes.The CCAAT sequence is a ubiquitous  In addition to the TATA-box, the CCAAT sequence is a ubiquitous cis-element of eukaryotic promoters that is present in the promoters of approximately 30% of eukaryotic genes2. Therefore, genes carrying a CCAAT-box are known to be primarily activated by conserved CCAAT-binding complexes in model eukaryotic organisms3.Gene expression is primarily orchestrated by a set of transcription factors that bind to 7. The heme activator protein (HAP) complex, which is also termed nuclear factor Y (NF-Y) or CCAAT-binding factor (CBF), was the first identified and is the most well studied CBC in various eukaryotic organisms. The Saccharomyces cerevisiae Hap complex consists of three essential CCAAT-binding factors  that are indispensable for CCAAT-binding activity9, orthologues of which  also comprise the mammalian CCAAT complex (NF-Y/CBF)10. Core elements of Hap3 and Hap5 display amino acid sequence similarities to the histone fold motifs of histones H2B and H2A, respectively, which are responsible for heterodimeric interactions. Another essential element of the complex, Hap2, contains a subunit association domain that allows for heterotrimer formation and nuclear localization signals (NLS)12. After the assembly of Hap2, Hap3, and Hap5, the heterotrimeric complex then recruits Hap4, an additional component that is only present in fungi, which allows for subsequent binding to the promoter of the target genes containing the CCAAT sequence12.The CCAAT-binding complex (CBC) typically consists of heterotrimeric core subunits and regulates primary/secondary metabolism, development, stress responses, and virulence in animals, plants, and fungiS. cerevisiae and Schizosaccharomyces pombe, as well as in plants and humans16. Pol ε plays crucial roles in chromosome replication, cell cycling, and the repair of damaged DNA17. Both Dpb3 and Dpb4 are non-essential proteins that form a heterodimeric complex and bind to double-stranded DNA20. The Dpb3-Dpb4 complex physically associates with the Pol ε catalytic subunit, Cdc20, and also interacts with proteins that are important for heterochromatin assembly. However, orthologues of Dpb3 and Dpb4 have rarely been identified in filamentous fungi to date.Similar to Hap5 and Hap3, two small components of DNA polymerase epsilon (Pol ε), DNA polymerase II subunit B3 (Dpb3) and Dpb4 are known that harbour H2A/H2B-like histone fold motifs in Aspergillus nidulans (AnCF) is involved in the utilization of carbon and nitrogen sources, and several enzyme-coding genes  are positively regulated by AnCF21. The Aspergillus oryzae HAP complex, AoCP, is a direct activator of the Taka-amylase A gene (taa)22. In addition, activation of the gene encoding the cellobiohydrolase II cellulose degrading enzyme (cbh2) is mediated by the Hap3 orthologue (HapC) in the biomass-degrading fungus Trichoderma reesei23. Recently, a few orthologues of HAP complex components and the histone-like protein have been characterized in plant pathogenic fungi, including Fusarium species26. These proteins are involved in pathogenesis, fungal development, and various biological processes, yet interactions between CCAAT-binding factors have not been investigated in plant pathogenic fungi, including F. graminearum.The HAP complex is responsible for global transcriptional activation, and several genes directly regulated by the HAP complex have been characterized in filamentous fungi. The HAP complex of F. graminearum is a prominent plant pathogen that causes Fusarium head blight (FHB) in cereal crops and ear and stalk rot on maize27, all of which result in severe yield losses and an accumulation of mycotoxins  that are harmful to animals and humans28. Previously, we performed a genome-wide functional analysis of the complete repertoire of transcription factor-encoding genes in F. graminearum29, which resulted in the identification of eight transcription factors containing CCAAT-binding domains29. Interestingly, while the phenotypes of F. graminearum strains mutated for six out of eight genes were not significantly different from those of the wild-type strain, the deletion of two putative CCAAT-binding transcription factors resulted in defects in fungal development, including increased sensitivity to DNA damaging agents30. Furthermore, a recent study revealed that the expression of FgHLTF1, one of the two CCAAT-binding factors involved in the DNA damage response, was downregulated by the putative type 2A phosphatase FgPpg1 and was shown to be associated with the high osmolarity glycerol (HOG) pathway24.The ascomycete fungus F. graminearum. Our results demonstrate that F. graminearum has two distinct CCAAT complex components containing histone-fold motifs, Fct1 and Fct2 (FgHltf1), which are required for DNA damage responses, sexual development, virulence, and trichothecene production. A protein-binding microarray analysis revealed that Fct2 binds to the consensus sequence CCAAT, and we also confirmed that Fct1 and Fct2 interact to form a complex. Moreover, this study provides the strong evidence supporting that the CCAAT-binding complex only has two distinct CCAAT-binding factors in F. graminearum.In this study, we attempted to characterize the CCAAT complex structure and its biological functions in F. graminearum30. Among them, strains carrying mutations in two CCAAT-binding factor-encoding genes, GzCCAAT002 (FGSG_01182) and GzCCAAT004 (FGSG_05304), were highly sensitive to DNA damaging agents compared to the wild-type strain. Recently, GzCCAAT004 was identified as a putative histone-like transcription factor, FgHLTF1, through a transcriptome analysis of a ΔFgppg1 strain24. In this study, we designated GzCCAAT002 and GzCCAAT004 as F. graminearumCCAAT-binding transcription factor 1 (FCT1) and FCT2, respectively. To generate complementation strains, the geneticin resistance gene cassette31 in each deletion mutant was replaced with FCT1 or FCT2 fused to the green fluorescent protein-encoding gene (GFP) and a hygromycin resistance gene cassette (HYG), yielding the strains FCT1c and FCT2c  or FCT2c-r  strains were generated via outcrosses between mat1r and FCT1c or FCT2c  analysis -based PBM analysis using the Fct2-DsRed fusion protein identified 4,526 putative DNA-binding sequences, with CCAATC as the predominant sequence , tryptophan (Trp), histidine (His), and adenine (Ade) (SD-LTHA)  Fig. .Table 2PF. verticillioides, A. nidulans, Neurospora crassa, S. pombe, and S. cerevisiae were performed  than Gzccaat6 and Gzccaat001, respectively. Fct1 and Fct2 were shown to be evolutionarily closer to Dpb4 and Dpb3, respectively, than the Hap complex components. Dpb3 and Dpb4, small components of yeast DNA polymerase epsilon (Pol ε) subunits, each have a H2A/H2B histone-fold motif and bind to DNA sequence as a complex20.Subsequently, phylogenetic analyses of the CCAAT-binding factors of med Fig. . GzccaatFCT1 and FCT2 for vegetative growth and sexual development, we compared the phenotypes of the deletion mutants with the wild-type and complementation mutant strains. The deletion mutants grew poorly on complete medium (CM) and minimal medium (MM), whereas complementation fully rescued the growth defects  and fct2-g  were generated via outcrossing of KM1934 with the fct1 or fct2 deletion mutants (Table FCTs and expresses cytosolic GFP) had spread to adjacent spikelets through rachis nodes  under our tested assay conditions.We hypothesized that if Fct1-Fct2 complex formation is crucial for the biological functions of these two proteins, then the phenotypic defects of the F. graminearum. Our biochemical, cytological, and genetic results demonstrated that the CCAAT-binding complex of F. graminearum comprises only two CCAAT-binding factors (Fct1 and Fct2) that are not highly conserved in other fungi or higher eukaryotes. Moreover, in-depth phenotypic analysis revealed that the Fct1-Fct2 complex is involved in various biological processes in F. graminearum, including vegetative growth, sexual reproduction, virulence, and mycotoxin production.In this study, we identified and characterized the CCAAT-binding transcription factors in the plant pathogenic fungus 37. Because each of these subunits is required for the DNA-binding activity of the complex, they are all essential for the function of the CCAAT-binding complex40. Biochemical studies of the interactions between these subunits has revealed that Hap3 and Hap5 form a tight dimer via a protein-protein interaction that is similar to the head to tail association of histones H2A/H2B and that this dimer offers a complex binding surface for Hap241. Interestingly, although the trimeric complex is sufficient to regulate gene expression in mammalian cells, orthologues of an additional component, Hap4 (HapX) or Hap4-like proteins, have been identified in fungi, including S. cerevisiae, S. pombe, Aspergillus, and Candida species44. Hap4 orthologues harbour a bZIP domain and a conserved 16-amino acid motif that is required for its interaction with the Hap2/Hap3/Hap5 complex. The Hap2, Hap3, and Hap5 complex assembles in the cytoplasm and is then transported to the nucleus via the nuclear localization signal (NLS) of Hap246. Subsequently, the heterotrimer complex binds to the promoters of target genes containing a CCAAT sequence and recruits Hap4 for subsequent gene activation46.In most eukaryotic organisms, the heme activator protein (HAP), also known as nuclear factor Y (NF-Y) or CCAAT-binding factor (CBF), is composed of three subunits: Hap2 , Hap3 , and Hap5 , indicating that this complex structure is evolutionally conserved in eukaryotes47. In addition to core histones, a similar secondary structure arrangement has been observed in several nuclear proteins involved in DNA metabolism, including TATA box-binding protein-associated factors, the DNA polymerase II subunits Dpb3 and Dpb4, and the CCAAT-binding complex proteins Hap3 (NF-YB) and Hap5 (NF-YC). The structure of the NF-YC-NF-YB complex resembles that of the H2A-H2B histone dimer48. Crystal structure analysis of the A. nidulans HAP complex showed that the complex specifically recognizes the CCAAT box of the promoter, and the S. cerevisiae Dpb3-Dpb4 heterodimer associates with double-stranded DNA without a preference for specific DNA sequences49. In this study, based on phylogenetic analysis, we determined that Fct1 and Fct2 are more closely related to Dpb4 and Dpb3, respectively, than to Hap complex components and that the two proteins interact with each other. In addition, protein binding microarray results showed that Fct2 specifically bound to the CCAAT sequence, unlike the Dpb3-Dpb4 complex, which binds to nonspecific double-stranded DNA. The deletion of FCT1 and FCT2, alone or in combination, resulted in an increased sensitivity of F. graminearum to DNA damaging agents. We speculate that Fct1 and Fct2 may be responsible for histone modification and DNA replication, although further investigation is needed to confirm this hypothesis.A histone fold is a structurally conserved motif identified near the C-terminus in core histones and is responsible for the ability of histones to bind and form heterodimersF. graminearum, among eight transcription factors identified as CCAAT-binding factors, Gzccaat001 (FGSG_00352), Gzccaat006 (FGSG_07087), and Gzccaat003 (FGSG_02608) are orthologous proteins of Hap2, Hap3, and Hap5, respectively -tagged histone H1 was used in the colocalization study. Minimal liquid medium supplemented with 5 mM agmatine (MMA) was used for the trichothecenes analysis56.All strains used in this study are listed in Table Fusarium laboratory manual54. Total RNA was isolated from mycelia ground in liquid nitrogen using an Easy-Spin Total RNA Extraction kit . Standard protocols were followed for restriction endonuclease digestion, agarose gel electrophoresis, and DNA gel blot hybridization with 32P labelled probes57. The PCR primers used in this study were synthesized at an oligonucleotide synthesis facility   of FCT1 or FCT2 in the F. graminearum wild-type strain Z-3639 were replaced with the geneticin resistance gene31 to create the deletion mutants. The fct1 and fct2 double mutant was generated by replacement of FCT2 gene with the hygromycin resistance gene (HYG) in the fct1 mutant. For the complementation and cellular localization assays, the 5′ flanking region, including the ORF with its own promoter, and the 3′ flanking region were amplified from genomic DNA of the wild-type strain using the primer pairs FCT1-5F/FCT1-5R GFP and FCT1-3F GFP/FCT1-3R, respectively. The GFP-HYG construct was amplified from the plasmid pIGPAPA using the primers pIGPAPA-sGFP/HYG-F1. The three amplicons were then fused via a second round of DJ PCR, after which the fusion constructs for transformation were amplified with nested primers using the second round PCR product as a template. Fungal transformation was performed as previously described55. The FCT2c strain, which was used to investigate cellular localization, was generated via the same strategy.The double-joint (DJ) PCR strategy was used to construct the fusion PCR products required to generate the targeted gene deletion and complementationMicroscopic observations were performed using a DE/Axio Imager A1 microscope  with the filter set 38HE  for GFP and the filter set 15  for RFP.34. Infected wheat heads were longitudinally dissected 6 days after inoculation and examined under a fluorescence microscope. Longitudinal sections cut through the centre of the spikelets were prepared freehand using a clean scalpel. The sectioned wheat heads were observed under reflected light and GFP fluorescence light (470 nm excitation and 525 nm emission wavelength filters) on a SteREO Lumar V12 microscope (Carl Zeiss).Wheat heads inoculated with the GFP-expressing strains were observed as previously described59. The full-length cDNA of FCT2 was inserted into the pET-DsRed expression vector to generate pET-Fct2Red, and the Fct2-DsRed fusion protein was expressed in the E. coli strain BL21-ColonPlus. Subsequently, the purified protein was incubated with a Q9 protein-binding microarray (Q9-PBM), which includes 232,145 quadruple probes, including 131,072 probes for all possible 9-mers, each of which was concatenated four times. Fluorescence images were captured using a GenePix 4000B microarray scanner . The consensus binding sequence was determined based on the fluorescence signal intensities according to previously described methods32.To determine the DNA-binding sequence of Fct2, a protein binding microarray assay was performed as previously described2HPO4, and 1.8 mM KH2PO4, pH 7.4) prior to resolving the proteins via SDS-PAGE (12%). The proteins separated via SDS-PAGE were digested with trypsin in situ and then analysed using a Q Exactive™ nano high resolution LC/MS MS spectrometer . The resulting peptide amino acid sequences from the LC-MS/MS data were identified in sequences in the Fusarium graminearum database (https://fungidb.org/)60. The results obtained for the wild-type strain were used as a negative control.To capture Fct2-interacting proteins, cell lysates prepared from two independent FCT2c strains were incubated with magnetic beads conjugated to a mouse anti-GFP antibody  following the manufacturer’s instructions. After incubating at 4 °C for overnight, the magnetic beads were washed six times with phosphate-buffered saline . After cotransformation of these vectors into S. cerevisiae NMY51 4- HIS3 ura3::(lexApo)8-lacZ ade2::(lexApo)8-ADE2 GAL4), a colony picked from the SD-Leu-Trp plates was grown in liquid SD-Leu-Trp medium, and the resulting cells were then spotted onto selective plates (SD-Leu-Trp-His-Ade). Strains carrying the empty vectors and pDL-Alg5 (−) were included as negative controls, while pAl-Alg5 (+) was included as a positive control.The Y2H assay was conducted using a DUALhunter kit  following the manufacturer’s instructions. To obtain cDNA, total RNA extracted from fungal cultures grown on carrot agar medium was reverse transcribed with SuperScriptIII reverse transcriptase . Each ORF was PCR amplified using primers with a SfiI restriction site (Supplementary Table 6 conidia/ml) obtained from a male strain.Aerial mycelia were removed from cultures grown on carrot agar medium for 5 days with 0.5 ml of a 2.5% Tween 60 solution to induce sexual reproduction. The plates were incubated under a near-UV light  at 25 °C for 7 to 10 days. For the outcrosses, mycelia from a female strain grown on carrot agar medium were fertilized with 1 ml of conidial suspension  were prepared for each strain, and 10 μl of each suspension was injected into the centre spikelet of a wheat head (cultivar: Eunpamil). After inoculation, the wheat plants were incubated in a humidified chamber for 3 days and then transferred to a greenhouse. Spikelets exhibiting disease symptoms were counted 21 days after inoculation. The experiment was performed with five replicate inoculations per strain, and two independent mutant strains were used for the experiment.For the virulence test, the point inoculation method was performed as previously described29. Briefly, MMA cultures were extracted with ethyl acetate, and the extracts were concentrated to dryness. A portion of each extract was derivatized with Sylon BZT  and analysed with a Shimadzu QP-5000 gas chromatograph mass spectrometer  using the relevant ion-monitoring mode as previously described61. The trichothecenes were quantified based on the biomasses produced by each strain, and the experiment was repeated three times.Trichothecene analysis was performed as previously describedCYP1) was used as an endogenous control for normalization. The qRT-PCR assay was repeated three times with three replicates per run, and the transcript levels relative to that of the housekeeping gene were expressed as 2−ΔΔCT31.Total RNA was prepared using an Easy-Spin Total RNA Extraction kit (Intron Biotech). The first strand cDNA was synthesized with SuperScriptIII reverse transcriptase (Invitrogen). Quantitative real-time PCR (qRT-PCR) was performed using SYBR Green Supermix  and a 7500 real-time PCR system  with the corresponding primers (Supplementary Table Supplementary information.