Coral reefs are among Earth’s best-studied ecosystems, yet the degree to which large predators influence the ecology of coral reefs remains an open and contentious question. Recent studies indicate the consumptive effects of large reef predators are too diffuse to elicit trophic cascades. Here, we provide evidence that such predators can produce non-consumptive (fear) effects that flow through herbivores to shape the distribution of seaweed on a coral reef. This trophic cascade emerged because reef topography, tidal oscillations, and shark hunting behaviour interact to create predictable “hot spots” of fear on the reef where herbivores withhold feeding and seaweeds gain a spatial refuge. Thus, in risky habitats, sharks can exert strong ecological impacts even though they are trophic generalists that rarely feed. These findings contextualize the debate over whether predators influence coral reef structure and function and move us to ask not if, but under what specific conditions, they generate trophic cascades. However, the ecological roles of most large predators remain unresolved, in part because they are disappearing from nature6 but also because they are large and mobile, making them difficult to study in a rigorous manner7. Indeed, even charismatic predators in well-studied ecosystems, like sharks on coral reefs, remain poorly understood8. While they and other large predators have increasingly become the focus of ecological studies in recent time, the degree to which sharks influence the general ecology of coral reefs remains an open question9.Large predators generate powerful trophic cascades within many of Earth’s ecosystems11, should exert strong consumptive effects that cascade to the base of the food web. Yet evidence for such effects is equivocal, even when considering reef systems where sharks remain abundant16. Equivocality may stem from differences between empirical and theoretical approaches, a focus on entire communities rather than a subset of strongly interacting species, or the fact that many seemingly pristine ecosystems are, in actuality, severely altered. Strong evidence for predator effects may also be elusive because coral reefs support complex food webs with high levels of species diversity, and potentially redundancy, within trophic levels, meaning that predator effects are dampened17 and unlikely to cascade under most scenarios12. Indeed, recent studies suggest that because reef sharks are generalist predators18 that hunt opportunistically within multiple reef habitats19, their consumptive effects are diffused across the food web and thus unlikely to cascade to impact the structure and function of the benthos8. However, as trophic generalists, sharks could create a strong fear of predation (non-consumptive effect) in some reef habitats20 such as shallow habitats where the chance of escape from a predator is reduced relative to deeper areas. Because fear effects amplify as they cascade, their ecological impacts often rival or exceed those of direct predation even where large predators consume few prey22.Many assume that reef sharks, like predators in less diverse ecosystems25. Also, some of these studies have focused on small site-attached herbivores26 rather than the large roving species that drive herbivory on coral reefs. As such, it remains unclear when or where large mobile predators may create fear effects that actually cascade to affect seaweed community structure and function. Theoretical and empirical studies from other ecosystems suggest that fear will cascade to shape plant communities in situations where landscape features interact with predator hunting behaviour to create areas or times of predictable risk (fear “hot spots”)28. Predictable fear hot spots diversify and structure plant communities by creating spatial escapes from herbivores where none would otherwise exist. If fear hot spots exist in some reef habitats, such as the shallow backreef, it would suggest that sharks and other large predators can play important ecological roles in these ecosystems, but that their ecological impacts are highly context-dependent. To-date, targeted investigations of this phenomenon are rare30. Here, we conducted observations and experiments in a shallow marine reserve in Fiji to explore whether large predators  create a trophic cascade through this very mechanism.Recent studies indicate that some coral reef herbivores reduce their feeding when in close proximity to reef predators or stationary predator decoys, but it is unclear if this fear causes only a temporary redistribution of herbivore feeding or an overall reduction in herbivoryPorites spp., branching Montipora spp., and tabular or branching Acropora spp.). It is also subject to large tides (maximum amplitude ~1.8 m). Consequently, the backreef has the following topology: (a) a contiguous upper reef surface (the “reef top”) that has grown to the mean low water mark in most places and is therefore only navigable by large herbivorous and piscivorous fishes at high tide ide Fig. . During in situ remote video, we discovered that blacktip reef sharks , whitetip reef sharks  and tawny nurse sharks  make daily excursions into the backreef and do so only during high tide  habitats32. Large jacks (Caranx ignobilis and C. melampygus) also make forays into the backreef at high tide, but were observed infrequently .Using ide Fig. , presumatly Fig. . Large a33. These sharks appear to have small home ranges35, with some individuals repeatedly visiting core areas on a daily or weekly basis34. They are also known from other ecosystems to predictably visit shallow lagoonal areas during high tide36. Nurse sharks consume primarily benthic invertebrates, but one-third of their diet is reef fishes37 and they overlap in diet niche space with blacktip and whitetip sharks18; thus, they too pose a predation threat to herbivorous fishes in shallow environments. Both jacks are also generalist piscivores; reef fish, including herbivores, can comprise 70–85% of their diet38. Therefore, tidal oscillations and predator movements interact in this backreef habitat to create a predation risk to herbivores that predictably cycles with the tide. This cycle of risk is generated almost entirely by sharks, as they accounted for ~85% of the predator sightings in our survey.Blacktip and whitetip reef sharks are large mesopredators that consume bony fishes (52 and 91% of diet respectively), including herbivorous fishes40. Such behaviours commonly drive trophic cascades27. We therefore hypothesized that herbivorous fishes, which shape seaweed community structure on most tropical Pacific reefs41, should forage intensely during low tide in these habitats (when risk is low) and reduce their foraging during high tide (when risk is high). To test this hypothesis, we conducted a series of experiments where we deployed two common brown seaweeds for 2 hours surrounding the peak of each tidal phase and assessed the rate at which they were consumed by fishes. Browsing herbivores rapidly consumed seaweeds in lagoons during low tide but foraged little during high tide  at times of high predation risk countered by energy acquisition (foraging) when safeide Fig. . When weide Fig. . Of the ide Fig. . Reef toNaso lituratus and N. unicornis  and the grazer C. spilurus were abundant in lagoons at low tide but were scarce (N. lituratus and N. unicornis) or half as abundant (C. spilurus) throughout the backreef at high tide (Table Naso spp.)42 appear to move into the backreef on the ebbing tide and strand themselves in the lagoons to feed; they then appear to leave the backreef as the tide rises . The other three key grazer species were equally abundant throughout the tidal cycle  at low tide was by the unicornfishes Turbinaria conoides, a brown seaweed consumed almost exclusively by N. lituratus and N. unicornis in this system42.Demonstration of a non-consumptive trophic cascade requires evidence that not only do herbivores alter their foraging in accordance with predation risk, but also that these actions flow on to shape plant community structure. If fear effects fail to propagate downward, one would predict upright fleshy seaweeds to be generally rare on healthy coral reefs since herbivory is intense in these ecosystems. By contrast, if fear effects flow to the base of the food web, one would expect a pattern of zonation at Votua whereby seaweeds are found in fear “hot spots” that serve as spatial escapes from herbivory  but are in low abundance elsewhere. To investigate whether seaweeds differed in abundance on reef tops vs. in lagoons (which at Votua are both hard-bottom substrates with no sand), we surveyed the seaweed community in three randomly selected lagoonal networks, comparing open substrates  on the reef top to equivalent substrates in adjacent lagoons. Seaweed biomass on the reef top was ~20 times greater than in hard-bottom lagoons, where seaweeds were virtually absent Fig. . Of the T. conoides) onto seaweed-free, hard-bottom substrates both in lagoons and on reef tops and assessed its growth (when caged) and loss to herbivores (when not caged) over 96 hours. Growth rates of T. conoides did not significantly differ between lagoons  and the reef top (where it is common)  between reef tops and lagoons could be important. Thus, to assess the alternative hypothesis that abiotic factors created the pattern of seaweed zonation we observed, we deployed the alga most common to the reef top , this seaweed-rich area receives little grazing or browsing Fig.  owing toconsumptive effects of predators (which are diffuse) and have generally done so using coarse community assemblage data. Thus, it remains unclear how much large predators may impact reef structure or function through direct versus indirect (fear) effects or how this may vary with location and habitat type. It is possible that predator effects can cascade, but happen through non-consumptive instead of consumptive mechanisms, and do so only in particular habitats and among a subset of strongly interacting species.There is little evidence that large predators consistently produce trophic cascades on coral reefs. However, past studies of trophic cascades in these ecosystems have largely focused on the 43, we found phenomenological evidence that sharks, via the fear they exert, can indirectly shape seaweed distribution in a shallow backreef habitat. Our findings extend those generated from studies employing predator decoys and statistical models26 to indicate that periodic visits by large predators can have lasting impacts on reef seaweed community structure, but only under certain contexts8. We show that where reefscape topography and tidal oscillations channel predator movements to predictable times and places , trophic cascades can arise. Such findings give context to the debate over whether trophic cascades can exist on coral reefs and move us to ask not if, but under what particular conditions, they might occur.By resolving reefscape effects and focusing on strongly interacting species28. For instance, trophic cascades are not expected on most deep forereefs, where predators abound and shelter availability and foraging risk do not vary with the tides. In such places reef shark encounters are less predictable and herbivore vigilance is eventually overridden by the need to acquire resources40. Indeed, forereefs where mesopredators abound are not overgrown by fleshy seaweeds44. By contrast, trophic cascades are more likely to exist in shallow backreef habitats or among lagoonal patch reefs where reefscape features and abundant predator populations create places and/or times of known risk to herbivores. Given the backreef we studied is typical of fringing reefs that surround high islands throughout the central and western tropical Pacific, we expect these trophic cascades to exist wherever similar biological and physical conditions occur throughout the region45.When and where trophic cascades arise will depend on how reefscape configuration, predator diversity, predator hunting mode, and prey behaviour interact to shape the rules of engagement between predators and prey22 but this and other reef studies30 provide reason to do so. At Votua, large predator movements appear to shift the timing with which herbivores visit and feed in the backreef, such that some herbivores of high food value  are concentrated in lagoons at low tide. Efficient human predators46 can easily harvest these large herbivores at low tide, since they have limited ability to escape. Indeed, outside of Votua Marine Reserve, human predators have dramatically reduced the abundance of all large herbivores in the backreef, triggering a phase shift to seaweed dominance within the fishing areas42. With knowledge of predator movements and resultant herbivore migrations, resource managers could mitigate this negative human impact in similar ecosystems by regulating not only where but when herbivores are harvested. Our example highlights the need to consider predator effects in ecosystem-based management47.Cascades of fear are rarely considered in resource management48 and montane forest51 ecosystems in that each involve large vertebrate carnivores and herbivores, are mediated in part by herbivore behaviour, and manifest through interactions with the landscape. While this sample size is small, the fact that such parallels exist among markedly different ecosystems raises the intriguing question of whether predators created important “landscapes of fear” in many of Earth’s ecosystems prior to the Anthropocene7. Unfortunately, such a question is difficult to answer because studies of trophic cascades involving large vertebrate predators have rarely been performed53, and humans have functionally eliminated large carnivores from many of Earth’s ecosystems7. For example, large apex predator sharks54 as well as the large mesopredator reef sharks studied here55 are now generally rare or absent on coral reefs exposed to heavy fishing pressure; thus, the effects we documented may already be extinguished from many places. Despite these difficulties we need to study Earth’s remaining wild places where predators still abound, and capitalize on chance events and variability in nature, if we are to reveal the ecological roles of predators2. Only then can we understand the ramifications of predator loss or recovery.The trophic cascade we describe here is similar to those in seagrassPorites spp., branching Montipora spp., and tabular or branching Acropora spp. corals, has grown vertically to meet the low tide limit in many places; however, the reef is interrupted regularly by deep, hard-bottom pavement areas (“lagoons”) that are populated by corals and that remain submerged throughout the tidal cycle . Typical of the fringing reefs that surround high islands in the tropical Pacific, the forereef at Votua grades steeply to a reef crest, then forms a shallow backreef lagoon that extends to shore Fig. . The bio56. Consequently, rates of browsing  and grazing (substrate cropping) by herbivorous fishes are high within the reserve and seaweeds are relatively scarce42. Reef sharks are also common to the reserve, in that they make daily forays into the backreef at high tide 38 are also seen in the backreef at high tide, though much less frequently  for six days – three in which high tide occurred in the morning and 3 in which it occurred in the afternoon - and scored the number of predator sightings in each video. We excluded videos from 1 August due to storm swell that interfered with camera deployment (thus n = 5 days). We screened each 2-hour video at 4x playback speed. Human activity was present in the field of view during the deployment of the assay ; we omitted this footage and waited for an additional ~30–60 seconds, after fishes in the field of view resumed their normal swimming and feeding behaviour, before we commenced scoring the video. We also excluded the footage (and the ~60 seconds before it) where humans entered the field of view to retrieve the assay. Humans were not otherwise present in the area during the assay. When a relevant predator was spotted in the field of view , we commenced normal playback speed and recorded the identity and size of the predator and the duration of its visit. As a conservative measure, in instances where it appeared that the same individual predator may have visited a single camera repeatedly during an assay, or visited several cameras in rapid succession, we scored the predator sighting once. Omitting this conservative measure would only strengthen the pattern we documented, as predators were observed exclusively at high tide  are encountered in the backreef as a function of tide, we deployed video cameras  for a 2-hour period surrounding the peak of each diurnal high and low tide every day  and, in a few instances, jacks (Caranx ignobilis and C. melampygus). Some may consider excluding N. ferrugineus from our survey because its diet consists primarily of invertebrates37. However, a large proportion (≥30%) of its diet is also reef fishes, it feeds at a high trophic level, and its niche overlaps with other piscivorous reef sharks37; hence, N. ferrugineus poses a potential threat to herbivorous fishes when encountered. For this reason, we retained N. ferrugineus sightings in our analysis. Even if we excluded nurse sharks from our analysis, the pattern we report  at high vs. low tide each day (n = 5) were compared with a paired t-test.Large predator sightings consisted primarily of sharks , it is unclear within this context whether herbivory rates vary with tidal phase. To quantify whether these herbivores change their rates of foraging throughout the tidal cycle , we conducted a series of feeding experiments where we documented rates of herbivory (browsing and grazing) on the reef as a function of tide  and space (reef top vs. lagoon). To avoid confounding tide with time of day, we replicated the experiment six times over two separate 3-day periods, one in which high tide occurred in the morning and the other in which high tide occurred in the afternoon. As with our predator surveys, we excluded all data from August 1 due to a storm that interfered with our ability to collect reliable data.Herbivorous fishes strongly influence algal abundance and distribution on most tropical Pacific reefsSargassum polycystum and Hormophysa cuneiformis) (a) in lagoons and on the reef top within 2 hours of peak high tide (n = 4 per location) and (b) in lagoons within 2 hours of peak low tide (n = 4) and measured the total amount of seaweed consumed by herbivores relative to caged seaweeds (controls) deployed in the same area. Seaweeds were not deployed on the reef top at low tide because this habitat is inaccessible to large herbivores at low tide. We used the seaweeds S. polycystum and H. cuneiformis in the assay because they are targeted by the same herbivores as Turbinaria conoides, the dominant alga on the reef tops in the reserve, but are consumed more rapidly to the extent that they are rare in the reserve and very common in the adjacent fished areas. This allowed us to make rapid assessments of browsing among the principal consumers of T. conoides without our assessments being confounded by background levels of the same seaweed in the environment. Seaweeds were spun 20 revolutions in a salad spinner and weighed before each experiment . Replicates consisted of a single thallus of each species, the holdfasts of which were woven ~15–20 cm apart into a 50 cm section of three-stranded nylon rope attached flush to the substrate. Replicates were deployed ≥10 m apart and dispersed among several lagoonal networks. Reef top deployments were positioned at least 0.5 m away from any lagoon edge and in areas devoid of seaweed so as to make them as apparent to herbivores as the seaweeds deployed in lagoons. A small cage containing the same amount of each seaweed species (weighed and roped as above) was also paired with each treatment replicate (≤3 m away) to control for any change in the mass of treatment seaweeds due to factors other than herbivory. Experiments were conducted during calm seas.Each day we deployed two common brown seaweeds ] − Tf, where Ti and Tf are the initial and final masses (respectively) of a seaweed exposed to herbivory and Ci and Cf are the initial and final masses (respectively) of its paired caged control. The total mass (S. polycystum and H. cuneiformis combined) of each replicate consumed per hour was calculated; rates were then averaged among replicates from each location and tide within a day to produce a daily average browsing rate for each location and tide (n = 5). To assess whether browsing in lagoons varied with tide, we compared the rate that herbivores consumed seaweed in lagoons at high vs. low tide each day with a paired t-test. To assess whether browsing in lagoons at high tide was less  within a 1 m2 area in front of each camera. We haphazardly selected a starting point in each video and scored 1 hour of footage, documenting the identity and size (to nearest 5 cm increment) of each nominally herbivorous fish that entered the 1 m2 area and the number of bites it took from the EAM. We excluded any footage interrupted by human activity as described above. While small size-class fish (juveniles) are a common component of reef shark diets18 and thus may be subject to fear effects [but see ref.25], their contribution to the process of herbivory on coral reefs is relatively minor58. Moreover, they are difficult to identify to species from video footage. Hence, individuals <10 cm in total length were not counted. The total number of bites by all herbivores in each 1-hour video was calculated; totals were then averaged among replicates from each location and tide within a day to produce a daily average grazing rate for each location and tide (n = 5). For the four herbivores found to be the predominant grazers during both tidal phases , we calculated species-specific grazing rates using the same approach. Community-level rates of grazing in lagoons at high vs. low tide each day were compared with a paired t-test. Likewise, rates of grazing in lagoons vs. on the reef top at high tide each day were compared with a paired t-test.To assess rates of grazing on the substratum (a process that prevents seaweed establishment), we deployed GoPro video cameras in front of reef substrate harbouring the epilithic algal matrix  during each 2-hour feeding experiment and recorded herbivore bites on the EAM (n = 4 cameras per location per tide per day). Of the cameras deployed at each location during each tide, we randomly selected and scored one replicate video. Thus, we scored five browsing videos per location and tide (1 per location per tide per day × 5 days = 5). For each video, in the first 60 minutes of footage absent human activity  we documented the identity and size (to nearest 5 cm increment) of each nominally herbivorous fish that fed from either S. polycystum or H. cuneiformis and the number of bites it took from each alga . We did not score fishes <10 cm total length for the reasons described above. We tabulated the total number of bites (S. polycystum and H. cuneiformis combined) taken by each fish species in each video so as to calculate species-specific browsing rates (bites per hour) for each location and tide (n = 5). However, we limited our comparison of browsing rates to those calculated for fishes in lagoons at low tide since 99% of browsing occurred during low tide.In addition to estimating the rate with which herbivores removed seaweed biomass during each tide (see section above), we also deployed GoPro video cameras in front of every browsing assay to document the identity of the herbivores responsible for seaweed removal and their relative importance to the process ; each row was set parallel to shore and separated by 10–20 m. The survey of lagoons at low tide consisted of six 30 × 5 m transects run along the middle contour of several large lagoonal networks, with the start and end of each transect spaced by ≥10 m. For each transect, a single snorkeler (A.S.H.) slowly swam while simultaneously deploying the transect tape and identified all nominally herbivorous fishes (families: Labridae (subfamily Scarinae), Acanthuridae, Siganidae, Kyphosidae) within the 5 m band and recorded their body length (to the nearest 5 cm size class category). The biomass of each individual was estimated from its length, using defined length-weight relationships; species biomass totals were summed for each transect. For species identified as key browsers and grazers in the system  at high vs. low tide was compared with a t-test or, where data were not normal but met the other assumptions of the t-test, a Mann-Whitney test59.To determine if herbivorous fishes alter their distribution depending on tidal state, we surveyed the abundance and size of herbivorous fishes across the available habitats at high and low tides: the entire reef at high tide and lagoons at low tide. The two surveys were both conducted within 2 hours of peak tide and at approximately the same time of day. To achieve similar timing, the survey of the backreef at high tide was conducted three days prior to the feeding experiments (see above) and a week prior to the lagoon survey. The survey of the backreef at high tide consisted of three “rows”  of four 30 × 5 m transects  vs. relative safety (lagoons). To do so, we scored the identity and biomass of seaweeds growing on the reef top and in adjacent lagoons in three sets of lagoonal networks. Lagoonal networks were haphazardly selected on Google Earth. These were separated by >200 m, not connected, and thus served as independent tests. Within the centre of each, we selected a random compass bearing and swam that bearing until we encountered the lagoon edge. At the edge, we deployed a 50 × 50 cm quadrat on the nearest reef top that was available for seaweed colonization . All upright seaweeds within the quadrat were harvested and bagged. We then deployed the quadrat in the nearest topographic low point of the adjacent lagoon (<1.5 m away) that was reef substrate available for seaweed colonization  and harvested seaweed from the quadrat. Ten paired surveys were conducted in each lagoonal network. Samples were immediately returned to the laboratory where they were sorted, identified to genus, and dried at 65 degrees Celsius to a constant mass. The total dry mass (grams ± 0.01) of seaweed on the reef top vs. in lagoons was compared for each site using a paired t-test, except in one instance (Site 1) where the data were not normal but did meet the other assumptions of the test; these were instead evaluated with a Wilcoxon testT. conoides, the most abundant alga on upper reef surfaces . In this experiment, we deployed replicate assays as pairs–one deployed on the reef top and the other <3 m away in an adjacent lagoon (n = 10 pairs)–and assessed the amount of T. conoides consumed by herbivores after 96 hours. Although seaweeds are commonly found on reef tops, we specifically selected areas on the reef top where seaweeds were rare or absent to reduce the potential for surrounding seaweeds to mask the presence of the experimental assay. Treatment replicates consisted of three seaweed thalli that were spun, weighed (mean wet mass ± s.e.m.: 27.12 ± 0.49 g), and woven 15 cm apart into a 50 cm section of three-stranded nylon rope. In addition, identical replicates (mean wet mass ± s.e.m.: 27.61 ± 0.49 g) were placed in cages and deployed within 1 m of each assay to (a) assess differences in T. conoides growth among locations and (b) account for mass changes in treatment seaweeds due to factors other than herbivory . Blocks of replicates were spaced 8–10 m apart, spanning a large interconnected network of lagoons. We calculated the amount of seaweed consumed by herbivores using the equation above. The rate that herbivores consumed T. conoides in lagoons vs. on the reef top, and the rate that caged T. conoides grew in lagoons vs. on the reef top, were each compared with a paired t-test.To investigate whether the seaweed zonation pattern we documented Fig.  was due Statistical analyses are described in detail within each section. Unless noted, data conformed to test assumptions. All tests were performed in SigmaStat v. 3.5 (Systat Inc.).Data reported in this paper are archived at Dryad (http://datadryad.org).All methods were carried out in accordance with relevant guidelines and regulations. Research was conducted under a research permit issued by the Fijian Government.Supplementary Information


While judging their sensory environments, decision-makers seem to use the uncertainty about their choices to guide adjustments of their subsequent behaviour. One possible source of these behavioural adjustments is arousal: decision uncertainty might drive the brain's arousal systems, which control global brain state and might thereby shape subsequent decision-making. Here, we measure pupil diameter, a proxy for central arousal state, in human observers performing a perceptual choice task of varying difficulty. Pupil dilation, after choice but before external feedback, reflects three hallmark signatures of decision uncertainty derived from a computational model. This increase in pupil-linked arousal boosts observers' tendency to alternate their choice on the subsequent trial. We conclude that decision uncertainty drives rapid changes in pupil-linked arousal state, which shape the serial correlation structure of ongoing choice behaviour. Decision uncertainty is often associated with higher order cognition and can impact choices. Here the authors show that post-decision pupil dilation scales with uncertainty and predicts a change in upcoming choice patterns. In perceptual and sensory-motor tasks, humans and animals behave as if they make use of decision uncertainty—the probability that a choice is correct, given the sensory evidence1214One prominent idea is that the brain broadcasts uncertainty signals across brain-wide neural circuits via low-level arousal systems464789101213Changes in central arousal state  are tightly coupled to fluctuations in pupil diameter under constant luminance131516171The model assumes that observers base their judgment of each stimulus on a noisy decision variable, sampled from a distribution that depends on the identity and strength of the stimulus . Two-alt219This model predicts three signatures of decision uncertainty225We systematically manipulated the strength of sensory evidence and tested whether pupil responses exhibited the three signatures derived above. We then quantified the predictive effects of pupil-linked arousal on subsequent behaviour in terms of the key elements of the perceptual decision process: response time (RT), perceptual sensitivity, lapse rate, and choice bias. Choice bias was decomposed into an overall bias for one choice, and a serial bias dependent on the history of previous choices or stimuli. We found a predictive effect of pupil-linked arousal responses on serial choice bias.Twenty-seven human observers performed a two-interval forced choice visual motion coherence discrimination task . As expeIn line with previous workThe pupil dilated during decision formation, peaking just after the choice (button press) as observed in previous workTo quantify the temporal evolution of uncertainty scaling in the pupil, we regressed baseline-corrected pupil time courses against each trial's evidence strength, separately for correct and error trials. From choice onwards, pupil dilation scaled positively with evidence strength on error trials, and negatively on correct trials . In otheThe pupil response also exhibited the other two signatures of decision uncertainty predicted by the model in r: 0.087 range: −0.042 to 0.302, for log-transformed RT). For all subsequent analyses reported in this paper, we removed RT-fluctuations from the trial-to-trial fluctuations of single-trial pupil responses via linear regression (see Methods).The scaling of the pupil response with decision uncertainty was not inherited from the analogous scaling of RT, but was also present after first removing (via linear regression) the trial-to-trial variations accounted for by RT . Indeed,We proceeded to test whether uncertainty-related pupil responses predicted changes in subsequent choice behaviour. It has been proposed that arousal signals control various aspects of learning and decision-making4678The pupil response predicted a reduction of serial choice bias . When a =0.939, P=0.398, Bf10=0.221; absolute value of overall bias: F=1.817, P=0.173, =1.936, P=0.155, =2.213, P=0.120, =3.232, P=0.048, Bf10=1.207; post-error slowing: F=2.056, P=0.138, P>0.05). The overall pattern of results implies that observers did not simply act more randomly after large pupil responses or RT. Random button presses would have reduced sensitivity, in other words, decreased the slope of the psychometric function, contrary to our observations ), neither overall choice bias , a good fraction tended to alternate their choices .The model fits revealed robust, and idiosyncratic, patterns of serial choice biases in most observers . The weir=0.010, P=0.960, Bf10=0.149) or stimulus weights . Likewise, the auto-correlation of absolute motion coherence differences  was close to 0 (range across observers: −0.061 to 0.028) and did not correlate with individual choice weights  or stimulus weights .Observers' serial choices biases were unrelated to the  serial correlations between stimuli. The transition probabilities between stimulus categories  were close to 0.5 (range across observers: 0.475–0.508), and did not correlate with individual choice weights  variance explained by pre-feedback pupil responses from the post-feedback pupil signal .While the modulatory effects associated with pupil responses and RT were both negative on average, such an overall reduction of the group-level repetition bias  might ber=0.017, P=0.935, Bf10=0.149). Further, the modulation weights were negative for both subgroups, and not significantly different between them , were negative only for the group of repeaters, and differed significantly between alternators and repeaters  scenarios. First, arousal responses might promote choice alternation at the level of response preparation, by altering the state of the motor system15Our current observations are not easily reconciled with existing theoretical accounts of the impact of phasic arousal on decision-making. One account posits that threshold crossing of the decision variable triggers phasic noradrenaline release, facilitating the translation of the decision into a behavioural response57Previous theories of arousal and neuromodulation have coarsely distinguished between two timescales of arousal fluctuations: tonic fluctuations over the course of seconds to hours, and phasic responses on a sub-second timescale, time-locked to rapid cognitive acts781379102942The dissociation between pupil- and RT-linked modulatory effects  on seria36613632In conclusion, our study identified decision uncertainty as a high-level driver of phasic arousal, and it uncovered a role of this pupil-linked arousal response in shaping the dynamics of serial choice biases—a pervasive but often ignored characteristic of human decision-making. These insights shed new light on the link between decision uncertainty, pupil-linked arousal state, and serial dependencies in decision-making. They set the stage for further investigations into the neural bases of arousal-dependent modulations of serial choice behaviour.N with μ. We estimated σ from the data using a probit psychometric function fit on data combined across observers. The probit slope β=0.367, where its inverse σ=2.723 reflected the standard deviation of the μ=−1 and μ=1 for weak evidence, and μ=−4 and μ=4 for strong evidence. To calculate the relationship between evidence strength and decision uncertainty  participated in the study. The ethics committee at the University of Amsterdam approved the study, and all observers gave their informed consent. We included all observers in each analyses presented in the paper. Each observer participated in one practice session and five main experimental sessions, each of approximately two hours and comprising 500 trials of the task. The number of observers was selected to allow for robust analyses of individual differences, as in previous pupillometry work from our laboratoryObservers performed a two-interval forced choice motion coherence discrimination task at constant luminance . ObserveThe difference between motion coherence of test and reference was taken from three sets: easy , medium  and hard . All observers started with the easy set. We switched to the medium set when their psychophysical thresholds (70% accuracy defined by a cumulative Weibull fit) dropped below 15%, and to the hard set when thresholds dropped below 10%, in a given session.Motion coherence differences were randomly shuffled within each block. We applied a counterbalancing scheme ensuring that within a block, each stimulus category (s2>or < s1) was followed by itself or its opposite equally often−1 in one of four diagonal directions . Signal dots that left the annulus wrapped around and reappeared on the other side. Signal dots had a limited ‘lifetime' and were re-plotted in a random location after being on the screen for four consecutive frames. Noise dots were assigned a random location within the annulus on each frame, resulting in ‘random position' noise with a ‘different' rule−1.Stimuli were generated using PsychToolbox-3 ref.  and presDue to the stochastic nature of the dynamic RDKs, the sensory evidence fluctuated within and across trials, around the nominal motion coherence level. To quantify behaviour and pupil responses as a function of the actual, rather than the nominal, single-trial evidence, we used motion energy filtering to estimate those fluctuationsTwo spatial filters, resembling weighted sinusoids in opposite phase, were defined byσg=0.05 and σc=0.35 defined the carrier sinusoid and the Gaussian envelope, respectively, in line with the response properties of MT neuronsx, y) was rotated to match the stimulus' target direction or its 180° opposite. Two temporal filters were defined bywhere k=60 reflected the envelope of the temporal filters, and ns=3 and nf =5 controlled the width of the slow and fast filters, respectivelyf1g1+f2g2 and f2g1–f1g2. We convolved each filter with the single-trial random dot movies. The resulting values were squared, and summed together across the two filterswhere This filtering procedure was performed for each observer's individual target direction as well as its 180° opposite. To avoid cardinal biases in motion perception, we used the four diagonals as target directions counterbalanced across observers. Outputs of the two filtering operations were subtracted to yield a direction-selective signal over timeObservers sat in a dark room with their head in a chinrest at 50 cm from the screen. Horizontal and vertical gaze position, as well as the area of the pupil, were monitored in the left eye using an EyeLink 1000 desktop mount . The eye tracker was calibrated before each block of 50 trials.z-scored per run, and resampled to 100 Hz. We epoched trials, and baseline corrected each trial by subtracting the mean pupil diameter 500 ms before onset of the reference stimulus.Missing data and blinks, as detected by the EyeLink software, were padded by 150 ms and linearly interpolated. Additional blinks were found using peak detection on the velocity of the pupil signal and linearly interpolated. We estimated the effect of blinks and saccades on the pupil response through deconvolution, and removed these responses from the data using linear regression using a procedure detailed in ref. r=−0.268, P=0.175, Bf10=0.369).We included all trials from all five main sessions  in the analyses reported in this paper. The time series of consecutive trial-wise stimuli, choices, RTs and pupil responses was necessary for the regression model of serial bias modulation. Observers were well-practiced in the task structure after the practice session. As a consequence, they made few blinks during the trial intervals . The percentage of interpolated trials did not correlate with the estimated effect of pupil responses on serial choice bias , and T denoted matrix transpose. The residual y′ thus reflected pupil responses, after removing variance explained by trial-by-trial RTs. This residual pupil response was used for all analyses reported in the main text.where We quantified post-error slowing, for tertiles of previous trial pupil responses, as described in ref. rt=1 on trial t was described asWe modelled the psychometric function  as folloλ and γ were the probabilities of stimulus-independent errors (‘lapses'), g(x)=1/(1+ex−) was the logistic function, α was perceptual sensitivity, and δ was a bias term. The free parameters γ, λ, α and δ were estimated by minimizing the negative log-likelihood of the data (using Matlab's fminsearchbnd). We constrained γ and λ to be identical, so as to estimate a single, choice-independent lapse rate.where δ was transformed from log-odds into probability by P=eδ/(1+eδ). This quantified P(rt=1) for ambiguous evidence . Collapsing these values across the two-choice options =(1–ex−) was the cumulative Weibull function, λ was the lapse rate, θ was the threshold indicating at which level of evidence strength an accuracy of ∼80% is achieved, and β was the slope of the cumulative Weibull function. The free parameters θ, β and λ were estimated by minimizing the negative log-likelihood of the data (using Matlab's fminsearchbnd). Perceptual sensitivity was then defined as 1/θ.where δhist(ht), which was a linear combination of previous stimuli and choicesWe modelled the pupil- and RT-linked modulation of serial choice bias by extending an established regression approachWithδ(ht) was the sum of the overall bias δ′ The history weights for past stimuli and responses allowed us to characterize different decision strategiesIn the upper and in the lower triangle, the magnitude of the stimulus weight is larger than the magnitude of the response weight, so strategies are dominated by the identity of the previous stimulus (which is only known to the observer as a function of their previous response and feedback). In the upper and lower triangle, strategies are thus defined by the sign of the stimulus weight. In the upper triangle stimulus weights are positive, indicating a tendency to repeat the previous stimulus. On a correct trial, previous choice and stimulus are equal and therefore, repeating the previous stimulus is equal to repeating the previous choice (a win-stay strategy). On errors, the previous choice is opposite to the previous stimulus and repeating the previous stimulus is equal to alternating the previous choice (lose-switch strategy). Conversely, in the lower triangle stimulus weights are negative, reflecting a tendency to alternate the previous stimulus. This implies a tendency to alternate the previous choice if the previous choice was correct (win-switch strategy) and a tendency to repeat the previous choice in case of a previous error (lose-stay strategy).The weights for previous choices and stimuli can easily be combined to obtain weights reflecting a tendency to repeat previous correct or incorrect choices . Specifi39P value was the fraction of permutations that exceeded the observed difference between the means. All P values reported were computed using two-sided tests.We used non-parametric permutation testing to test for the group-level significance of individually fitted parameter values  and 5e,g10 quantifies the evidence in favour of the null or the alternative hypothesis, where Bf10 < 1/3 or>3 is taken to indicate substantial evidence for H0 or H1, respectively. Bf10=1 indicates inconclusive evidence. We similarly computed Bf10 for correlations, based on the Pearson correlation coefficientIn P-value for the difference between the two correlation coefficients (choice weight by pupil modulation weight vs choice weight by RT modulation weight), shown in The http://dx.doi.org/10.6084/m9.figshare.4300043.All raw and processed data, as well as the code to reproduce all analyses and figures, are available at How to cite this article: Urai, A. E. et al. Pupil-linked arousal is driven by decision uncertainty and alters serial choice bias. Nat. Commun.8, 14637 doi: 10.1038/ncomms14637 (2017).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.Supplementary Figures


Neurosteroids, comprising pregnane, androstane, and sulfated steroids can alter neuronal excitability through interaction with ligand-gated ion channels and other receptors and have therefore a therapeutic potential in several brain disorders. They can be formed in brain cells or are synthesized by an endocrine gland and reach the brain by penetrating the blood–brain barrier (BBB). Especially sulfated steroids such as pregnenolone sulfate (PregS) and dehydroepiandrosterone sulfate (DHEAS) depend on transporter proteins to cross membranes. In this review, we discuss the involvement of ATP-binding cassette (ABC)- and solute carrier (SLC)-type membrane proteins in the transport of these compounds at the BBB and in the choroid plexus (CP), but also in the secretion from neurons and glial cells. Among the ABC transporters, especially BCRP (ABCG2) and several MRP/ABCC subfamily members  are expressed in the brain and known to efflux conjugated steroids. Furthermore, several SLC transporters have been shown to mediate cellular uptake of steroid sulfates. These include members of the OATP/SLCO subfamily, namely OATP1A2 and OATP2B1, as well as OAT3 (SLC22A3), which have been reported to be expressed at the BBB, in the CP and in part in neurons. Furthermore, a role of the organic solute transporter OSTα-OSTβ (SLC51A/B) in brain DHEAS/PregS homeostasis has been proposed. This transporter was reported to be localized especially in steroidogenic cells of the cerebellum and hippocampus. To date, the impact of transporters on neurosteroid homeostasis is still poorly understood. Further insights are desirable also with regard to the therapeutic potential of these compounds. A receptor , androstane neurosteroids , and sulfated compounds [PregS and DHEAS] . They careceptor  and to breceptor . Furtherreceptor .Figure 1).While the serum concentrations of the non-sulfated DHEA and pregnenolone are in the low nM range in men and women , levels ATP-binding cassette proteins can mediate a unidirectional primary active transport of a variety of compounds across membranes. Among the ABC transporters especially ABCG2, also known as the BCRP, and several ABCC/MRP subfamily members are known efflux pumps for conjugated steroids .1-3-S and DHEAS, but not unconjugated or glucuronidated steroids . In addition, androgens such as dihydrotestosterone (DHT) have been identified as BCRP substrates  was identified as second export pump conferring a multidrug resistance phenotype besides the MDR1/P-glycoprotein (ABCB1) . MRP1 wat manner  and is et manner . It is at manner ; howevert manner , but alst manner . Some grt manner . Becauset manner  and the t manner . Thus, it manner . Howevert manner . MRP1 ant manner . Immunost manner , but wast manner . Similart manner .m of 2 μM; A more relevant efflux transporter for conjugated steroids in the brain may be MRP4/ABCC4, which exhibits a unique broad substrate specificity. MRP4 shows the remarkable capacity to transport cyclic nucleotides and MRP4 has been established as an independent regulator of intracellular cAMP levels in several cell types . Furtherm value of 13–21 μM, whereas the Km was above 150 μM for MRP8-mediated transport of E1-3-S  may be relevant with respect to neurosteroid transport. MRP8 was shown to transport DHEAS in isolated membrane vesicles with a Kf E1-3-S . In immuf E1-3-S . In addif E1-3-S .Besides ABC-type efflux transporters, neurosteroid concentrations in the brain may also be modulated by uptake transporters. Since several members of the SLC superfamily have been identified as uptake transporters for steroid conjugates in general, these transporters are interesting candidates for the transport of neurosteroids. In fact, several SLCs have been shown to mediate cellular uptake of DHEAS and PregS.1-3-S  or estradiol-17β-glucuronide  and the neurosteroid DHEAS  (Table 1) of the physiological plasma concentration  family is probably the most interesting one in this context. In humans, 11 SLCO transporters exist, organized in six families . The phyOATP2B1) . The afffampicin . Assuminfampicin , changesfampicin . Since Ofampicin . In addifampicin . Besidesfampicin . Like fofampicin  first refampicin . Interesesterone . Under testerone . PregS testerone . This fiesterone . Due to f the CP .m: 1.5 μM (DHEAS) and 6.9 μM (PregS)]  with several further organic anion transporters has been reported. For example, both sulfated neurosteroids have been shown to be transported with high affinity by the organic solute transporter OSTα-OSTβ [K(PregS)] . The het(PregS)] . In the (PregS)] . Both re(PregS)] .A third group of SLC transporters involved in the CNS distribution of sulfated neurosteroids are the organic anion transporters (OATs), which are part of the SLC22A branch . The pivThe detailed functions of the described ABC and SLC transporters in brain are still poorly understood. Even data on the expression and localization, e.g., at the BBB are often controversial. Knock-out mice of the ABC and some SLC transporters are available, but have been mainly used to study the role of these transporters for brain penetration of certain drugs . These sFigure 1 and revised the manuscript. All authors read and approved the manuscript for publication.MG and GJ conceived and wrote the manuscript. PH designed 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.


Alphavirus nucleocapsids are assembled in the cytoplasm of infected cells from 240 copies of the capsid protein and the approximately 11 kb positive strand genomic RNA. However, the challenge of how the capsid specifically selects its RNA package and assembles around it has remained an elusive one to solve. In this review, we will summarize what is known about the alphavirus capsid protein, the packaging signal, and their roles in the mechanism of packaging and assembly. We will review the discovery of the packaging signal and how there is as much evidence for, as well as against, its requirement to specify packaging of the genomic RNA. Finally, we will compare this model with those of other viral systems including particular reference to a relatively new idea of RNA packaging based on the presence of multiple minimal packaging signals throughout the genome known as the two stage mechanism. This review will provide a basis for further investigating the fundamental ways of how RNA viruses are able to select their own cargo from the relative chaos that is the cytoplasm. Alphavirus is one of two genera within the family Togaviridae. Alphaviruses are ubiquitous small enveloped RNA viruses [Aedes). There are currently 31 distinctive members, which are unofficially categorized as either old world or new world depending on geographic identification [The genus  viruses . They ha viruses . These vfication ,5. Despification ,7,8. In T = 4 icosahedral symmetry  have been generated from the heterologous expression of the structural proteins in both insect and mammalian cells ,70,71. TFollowing their identification of the VEEV PS, Frolov and co-workers sought to characterize the mechanism of packaging in cell culture by extensively mutating the N-terminus of the CP. One of the most compelling results was that mutagenesis of all the positively charged amino acids still resulted in virus particle formation, albeit ones that packaged predominantly subgenomic RNA. These particles were termed pseudoinfectious viruses (PIVs) owing to their dramatically decreased infectivity . Upon paOverall, these results support the hypothesis that the positively charged N-terminus is not the only determinant of packaging. This domain does however form critical interactions for selecting the viral RNA and then proceeding with its assembly. The data suggests that adjacent C-terminal interactions can be sufficient to result in assembly in a cellular context even if the positive charge of the N-terminus is negated. They also suggest that location in the cell may play a role since subgenomic and not cellular RNA was packaged in many of the mutants described above. This was subsequently addressed in a paper in which revertants to the PIV particles were characterized. A series of reversions occurred in the replication protein nsP2, which improved viral fitness and suggested that nsP2 may influence RNA packaging . The obsFor a long time, the pre-formation of NCs in the cytoplasm was an assumed feature of the assembly process. However, various lines of evidence suggest that alphaviruses can also follow a pathway in which budding and assembly occurs simultaneously. This was first revealed via mutations to the conserved domain of SFV , Hepatitis C virus (HCV), and members of the aviridae ,95,97,98aviridae . This suTherefore, the detailed molecular mechanisms describing alphavirus NC genome packaging and assembly remain elusive. Traditional approaches have identified some viruses with singular RNA secondary structures, described as a PS, which are able to nucleate CPs. This initiates an electrostatically driven assembly process. However, many viruses do not conform to this model as a single PS could not be identified. For these, the newer two stage theory appears more valid in that multiple PSs achieve assembly by guiding the capsid protein down a specific RNA packaging pathway. The real answer may lie in some combination of the two theories and further investigation into alphavirus assembly may be a useful system to investigate this. Given the recent advances in structure determination using cryo-EM, it may be worth revisiting the structure of the alphavirus NC and designing experiments to determine whether specific RNA sequences make contacts with the N-terminal domain. In a truly electrostatic mechanism, it is unlikely that a specific sequence would be necessary. Additional questions about alphavirus assembly include investigating the site of NC assembly within the cellular context. The prevailing hypothesis is that assembly occurs in or near replication spherules as they are the most obvious place where CP could find genomic RNA. However, specific evidence to support this idea is lacking. The current evidence indicates that spherules begin biogenesis at the PM and then become CPVIs. A question is raised whether CPVIs are required for NC assembly or whether spherules at the PM play any role in the alternative assembly model from the PM. It is also important to determine how the CP or genome RNA traffics to sites of assembly. Unpublished data in our laboratory suggest that intermediate filaments provide a network on which NCs traffic between CPVIs and IIs. There is also a line of research dedicated to understanding the role of the CP upon entry into new cells. Evidence from Sokoloski et al., 2017, suggests that specific CP-RNA interactions generated during assembly or upon disassembly can alter the kinetics of viral growth in a subsequent cell . More di


We found a broad spectrum of uridylated RNAs including rRNAs, snRNAs, snoRNAs, tRNAs, vault, 7SL, Y RNAs, mRNAs, lncRNAs, and transcripts from pseudogenes. The unifying features of most of these identified RNAs are aberrant processing and the presence of stable secondary structures. Most importantly, we demonstrate that uridylation mediates DIS3L2 degradation of short RNA polymerase II‐derived RNAs. Our findings establish the role of DIS3L2 and oligouridylation as the cytoplasmic quality control for highly structured ncRNAs.Uridylation of various cellular RNA species at the 3′ end has been generally linked to RNA degradation. In mammals, uridylated pre‐let‐7 miRNAs and mRNAs are targeted by the 3′ to 5′ exoribonuclease DIS3L2. Mutations in DIS3L2 have been associated with Perlman syndrome and with Wilms tumor susceptibility. Using  We thereby identified an extensive set of uridylated RNAs including non‐coding RNAs such as the small nuclear (sn)RNAs, ribosomal (r)RNAs, transfer (t)RNAs, long non‐coding (lnc)RNA, vault RNAs, Y RNAs, micro(mi)RNAs, mRNAs, and transcription start site‐derived RNAs from protein‐coding gene loci. Together with the biochemical evidence presented here as well as what we previously demonstrated, these data indicate that TUT‐DIS3L2 are part of a general mechanism of cytoplasmic RNA surveillance and degradation in mammalian cells.In a previous study  as a substrate : (i) close proximity to mRNA transcription start sites (TSS), (ii) frequent spanning to introns, and (iii) binding of DIS3L2 to U+ 5′ mRf did not correlate with changes in respective mRNA expression upon DIS3L2 inactivation Fig C. TSSas et al, et al, et al, et al, Eukaryotic cells have evolved a number of mechanisms for RNA quality control, which come into play when faulty transcription or processing leads to aberrant RNAs. Here, we reveal for the first time an extensive catalog of oligouridylated mammalian RNAs. Moreover, we show that TUTase‐DIS3L2 Surveillance (TDS) is a general pathway of cytoplasmic quality control for structured, mammalian ncRNAs. Uridylation and DIS3L2 were previously implicated in the rapid mRNA turnover in response to various stresses, such as viral infections or apoptosis  stretches on these transcripts rarely extended beyond the genome‐encoded U tract. Thus, it is possible that terminators may serve as a signal for DIS3L2 targeting. During the revision process of this manuscript, a study was published also showing that uridylation and DIS3L2 mediate quality control of non‐coding RNAs, such as snRNAs or Y RNAs  was ligated to the bound RNA with T4 RNA ligase (Fermentas) in buffer containing 25% PEG 8000 at 16°C overnight. Protein–RNA complexes were resolved on a 4–12% gradient SDS–PAGE , and the region corresponding to the region above migration position of DIS3L2‐Flag was cut out from the gel and eluted with proteinase K‐containing elution buffer  at 50°C for 2 h. RNAs were then ligated to the 3′ adaptor (5′‐rAppAGATCGGAAGAGCACACGTCT‐NH2‐3′). RNA was size fractionated on 8% polyacrylamide/8 M urea gel. RNA fragments of the length of 70–110 nt were excised and extracted from the gel. Reverse transcription was done with a 3′ primer (5′‐AGACGTGTGCTCTTCCGATCT‐3′) and Superscript III reverse transcriptase (Invitrogen). The resulting cDNA was used as a template for PCR amplification (5′ Primer: 5′‐AATGATACGGCGACCACCGAGATCTACACGTTCAGAGTTCTACAGTCCG‐s‐A‐3′). The PCR products were sequenced on the Illumina 2000 sequencer.For the CLIP analysis, we used the previously described stable cell line of human embryonic kidney cells  with inducible expression of human catalytically inactive form of DIS3L2 D391N that possess C‐terminal fusion 3xFlag tag : tRNA → miRNA → snRNA → 5S rRNA → miscRNA → snoRNA → mRNA → lincRNA. The tRNA and miRNA genes were annotated with miRBase . For purification of FLAG‐DIS3L2, 100 μl of anti‐FLAG M2 beads (Sigma‐Aldrich) washed with lysis buffer was incubated with cell extracts for 1 h in a cold room rotating. Beads were extensively washed with 10 volumes of wash buffer . Depending on the downstream application, proteins were eluted with one volume of 3×FLAG peptide (Sigma‐Aldrich) resuspended in lysis buffer or by boiling with SDS loading buffer for 5 min.Cells were resuspended in 4 ml of ice‐cold lysis buffer ) and incubated rocking at 4°C for 15 min. Lysate was cleared by centrifugation . Cells were lysed in buffer containing 150 mM NaCl, 50 mM Tris pH 7.6, 0.5% Triton X‐100, supplemented with protease inhibitors , 0.5 mM EDTA, 1 mM DTT, RNasin (Promega). Lysates were cleared by centrifugation, and supernatants were applied on FLAG M2 Magnetic beads (Sigma) and incubated for 60 min. The bound fractions were washed two times with lysis buffer containing 150 mM NaCl and two times with 300 mM NaCl. RNA was eluted by treating whole beads with 2 mg/ml proteinase K (NEB) for 120 min at 37°C and subsequently phenol/chloroform extracted and ethanol precipitated.et al  were cloned in pSpCas9n vector. We applied the double nickase technology using several pairs of CRISPRs to reduce the amount of off‐target effects . The disruption of the open reading frame in mutant DIS3L2 mRNA was confirmed by direct measurement of DIS3L2 protein expression by Western blot.DIS3L2 knockout (K.O.) HEK293T cell line was prepared by using CRISPR/Cas9 technology as described in Ran et al . Briefly2. Overexpression of Dis3L2 WT and DIS3L2 MUT were induced with 100 ng/ml of doxycycline for 24 h. Total RNA was isolated with TriPure Isolation Reagent (Roche) according to manufacturer's instructions, followed by RNase‐free TURBO DNase (Ambion) treatment. Ribosomal RNA was depleted from 4 μg of total RNA treated with TURBO DNase using the RiboMinusTM Eukaryote System v2 (Ambion) following the manufacturer's procedure. Efficiency of rRNA removal and concentration of rRNA‐depleted RNA was monitored by Bioanalyzer 2100 (Agilent Technologies) using RNA 6000 Pico Kit. Sequencing libraries for whole transcriptome analysis were prepared using ScriptSeq™ v2 RNA‐Seq Library Preparation Kit (Epicentre Biotechnologies) following the manufacturer's procedure. After the 3′‐terminal tagging, the di‐tagged cDNA was purified using MinElute PCR Purification Kit (Qiagen). Three 6‐base index sequences were used to prepare bar‐coded libraries for sample multiplexing (ScriptSeq™ Index PCR Primers (Set 1); Epicentre Biotechnologies). PCR was carried out through 15 cycles to generate the second strand of cDNA, incorporate barcodes, and amplify libraries. A concluding Bioanalyzer 2100 run with the High Sensitivity DNA Kit (Agilent Technologies) that allows the analysis of DNA libraries regarding size, purity, and concentration completed the workflow of library preparation. The three RNA‐seq libraries were then multiplexed in a single lane and sequenced on an Illumina HiSeq2000 using 50‐bp single‐end sequencing chemistry.The control HEK293T‐Rex FlipIn cells, and cells overexpressing WT or mutant DIS3L2, and DIS3 K.O., were maintained in Dulbecco's modified Eagle's medium (DMEM), supplemented with 10% fetal calf serum at 37°C in the presence of 5% COet al, et al, et al, Raw reads were subjected to adapter trimming using the tool cutadapt Martin, . ProcessTotal RNA was resolved on 10% denaturing polyacrylamide gel and transferred to Hybond‐N+ membrane  by electroblotting (Bio‐Rad). The hybridization with radioactively labeled oligonucleotides was performed in ULTRAhyb‐oligo hybridization buffer (Ambion) at 38°C. Prior to addition of the labeled probe, the membrane was prehybridized at 42°C for 2 h. The radioactive signal was monitored by phosphorimager FLA‐9000 (FUJIFILM). Quantification of signals was done using Multi Gauge software v3.2 (FUJIFILM).g, 4°C, 8 min.). The remaining small RNA in the supernatant was then precipitated with 0.7 volumes of isopropanol at 4°C for 30 min. followed by centrifugation . Small RNA fraction was treated with Turbo DNase (Ambion) extracted by phenol/chloroform and precipitated by isopropanol. 3′ pre‐adenylated DNA linker ligation was performed using T4 RNA Ligase2, truncated K227Q (New England BioLabs) according to manufacturer's instructions. Briefly, 2 μg of small RNA was incubated with 2 μl of 10 μM L3AppDNA linker  and 200 U of the ligase in 20 μl of total reaction volume at 16°C overnight. RNA was reverse‐transcribed with SuperScript RTIII (Invitrogen) using RT‐CLIP2 primer and PCR amplified with gene‐specific primers  using TriPure Isolation Reagent (Roche) followed by selective RNA precipitation. Fraction of RNA larger than 500 nt was first precipitated with 0.5 volume of 75% EtOH at room temperature for 10 min, followed by centrifugation  and reverse‐transcribed for 50 min. at 60°C using TGIRT‐III (InGex) and RT‐CLIP2 primer following manufacturer's instructions. PCR was performed with RT‐CLIP2 and indicated gene‐specific primers .2 in 1× NEH buffer) and incubated gently rocking at 4°C for 10 min. The released cytoplasmic fraction was collected from the dish and cleared by centrifugation at 500 g for 3 min. 1.5 ml TRI‐reagent LS (Sigma) was added to 500 μl of the supernatant for subsequent isolation of the small RNA by selective precipitation as described above. Residues of the cells on the dish were washed with ice‐cold 1× PBS and collected by scrapping in 1 ml of Buffer 2 . After 30‐min incubation on ice, nuclei were pelleted by centrifugation at 7,000 g for 15 min. The supernatant, which contained other organelles, was transferred to a new tube. The pellet was washed with cold 1× PBS and kept as the nuclear fraction. An aliquot from each fraction was used for a Western blot analysis. The cytoplasmic, nuclear, and organellar fractions were then used for small RNA isolation by selective precipitation as described above.Subcellular fractionation was performed with minor modifications as described in Holden & Horton  and Liu et al  XP rabbit monoclonal Ab, Cell Signalling Technologies, cat. no. 6571; anti‐DDX5 (D15E10) XP rabbit monoclonal Ab, Cell Signalling Technologies, cat. no. 9877; anti‐rabbit IgG HRP polyclonal secondary Ab, Promega, cat. no. W4011; anti‐mouse IgG HRP polyclonal secondary Ab, Promega, cat. no. W4021; anti‐DIS3L2 rabbit polyclonal Ab, produced by Moravian Biotechnology, assay (WB) specific test in Ustianenko et al .Raw and processed data of CLIP and RNAseq experiments can be found in GEO database under accession code GSE81537.SV conceived, designed and interpreted experiments, and supervised the project. DU performed, analyzed, and interpreted the CLIP‐seq analyses, JP designed and performed the bioinformatics analyses, ZF performed CLIP‐seq validation experiments of ncRNAs and TSSas and helped with the manuscripts preparation, LB performed initial bioinformatics analyses, DZ performed cell fractionation and subsequent RNA analyses, and AF prepared stable cell lines, RNAs, and cDNA libraries for high‐throughput sequencing. MZ helped with the design and interpretation of bioinformatics analyses and manuscript preparation. SV, DU, and JP wrote the manuscript.The authors declare that they have no conflict of interest.AppendixClick here for additional data file.Expanded View Figures PDFClick here for additional data file.Table EV1Click here for additional data file.Review Process FileClick here for additional data file.Source Data for Figure 4Click here for additional data file.