RNAslider: a faster engine for consecutive windows folding and its application to the analysis of genomic folding asymmetry

<p>Abstract</p> <p>Background</p> <p>Scanning large genomes with a sliding window in search of locally stable RNA structures is a well motivated problem in bioinformatics. Given a predefined window size L and an RNA sequence S of size N (L < N), the consecutive windows folding problem is to compute the minimal free energy (MFE) for the folding of each of the L-sized substrings of S. The consecutive windows folding problem can be naively solved in O(NL³) by applying any of the classical cubic-time RNA folding algorithms to each of the N-L windows of size L. Recently an O(NL²) solution for this problem has been described.</p> <p>Results</p> <p>Here, we describe and implement an O(NLψ(L)) engine for the consecutive windows folding problem, where ψ(L) is shown to converge to O(1) under the assumption of a standard probabilistic polymer folding model, yielding an O(L) speedup which is experimentally confirmed. Using this tool, we note an intriguing directionality (5'-3' vs. 3'-5') folding bias, i.e. that the minimal free energy (MFE) of folding is higher in the native direction of the DNA than in the reverse direction of various genomic regions in several organisms including regions of the genomes that do not encode proteins or ncRNA. This bias largely emerges from the genomic dinucleotide bias which affects the MFE, however we see some variations in the folding bias in the different genomic regions when normalized to the dinucleotide bias. We also present results from calculating the MFE landscape of a mouse chromosome 1, characterizing the MFE of the long ncRNA molecules that reside in this chromosome.</p> <p>Conclusion</p> <p>The efficient consecutive windows folding engine described in this paper allows for genome wide scans for ncRNA molecules as well as large-scale statistics. This is implemented here as a software tool, called RNAslider, and applied to the scanning of long chromosomes, leading to the observation of features that are visible only on a large scale.</p

Period 2: A Regulator of Multiple Tissue-Specific Circadian Functions

The zebrafish represents a powerful model for exploring how light regulates the circadian clock due to the direct light sensitivity of its peripheral clocks, a property that is retained even in organ cultures as well as zebrafish-derived cell lines. Light-inducible expression of the per2 clock gene has been predicted to play a vital function in relaying light information to the core circadian clock mechanism in many organisms, including zebrafish. To directly test the contribution of per2 to circadian clock function in zebrafish, we have generated a loss-of-function per2 gene mutation. Our results reveal a tissue-specific role for the per2 gene in maintaining rhythmic expression of circadian clock genes, as well as clock-controlled genes, and an impact on the rhythmic behavior of intact zebrafish larvae. Furthermore, we demonstrate that disruption of the per2 gene impacts on the circadian regulation of the cell cycle in vivo. Based on these results, we hypothesize that in addition to serving as a central element of the light input pathway to the circadian clock, per2 acts as circadian regulator of tissue-specific physiological functions in zebrafish

A Zebrafish Model for a Rare Genetic Disease Reveals a Conserved Role for FBXL3 in the Circadian Clock System

The circadian clock, which drives a wide range of bodily rhythms in synchrony with the day–night cycle, is based on a molecular oscillator that ticks with a period of approximately 24 h. Timed proteasomal degradation of clock components is central to the fine-tuning of the oscillator’s period. FBXL3 is a protein that functions as a substrate-recognition factor in the E3 ubiquitin ligase complex, and was originally shown in mice to mediate degradation of CRY proteins and thus contribute to the mammalian circadian clock mechanism. By exome sequencing, we have identified a FBXL3 mutation in patients with syndromic developmental delay accompanied by morphological abnormalities and intellectual disability, albeit with a normal sleep pattern. We have investigated the function of FBXL3 in the zebrafish, an excellent model to study both vertebrate development and circadian clock function and, like humans, a diurnal species. Loss of fbxl3a function in zebrafish led to disruption of circadian rhythms of promoter activity and mRNA expression as well as locomotor activity and sleep–wake cycles. However, unlike humans, no morphological effects were evident. These findings point to an evolutionary conserved role for FBXL3 in the circadian clock system across vertebrates and to the acquisition of developmental roles in humans

Data from: Vertical exploration and dimensional modularity in mice

Exploration is a central component of animal behaviour studied extensively in rodents. Previous tests of free exploration limited vertical movement to rearing and jumping. Here we attach a wire mesh to the arena wall, allowing vertical exploration. This provides an opportunity to study the morphogenesis of behaviour along the vertical dimension, and examine the context in which it is performed. In the current setup, the mice first use the doorway as a point reference for establishing a borderline linear path along the circumference of the arena floor, and then use this path as a linear reference for performing horizontal forays towards the center (incursions) and vertical forays on the wire mesh (ascents). Vertical movement starts with rearing on the wall, and commences with straight vertical ascents that increase in extent and complexity. The mice first reach the top of the wall, then mill about within circumscribed horizontal sections, and then progress horizontally for increasingly longer distances on the upper edge of the wire mesh. Examination of the sequence of borderline segments, incursions and ascents reveals dimensional modularity: an initial series ("bout") of borderline segments precedes alternating bouts of incursions and bouts of ascents, thus exhibiting sustained attention to each dimension separately. The exhibited separate growth in extent and in complexity of movement and the sustained attention to each of the three dimensions disclose the mice's modular perception of this environment and validate all three as natural kinds

Vertical exploration data

This .rar contains all required data for Vertical exploration and dimensional modularity in mice. The directory "Track Data" and its subdirectories contain CSV files for all mice with the 2D tracking coordinates calculated in Ethovision XT. The directory "RSEE data" and subdirectories contain Rdata files for all mice with initial data preparation. The directory "Individual Analysis Data" and its subdirectories contain Rdata files for all mice with analysis results

Code

R code for the data preparation and analysis performed in the paper, including the modified arena builder algorithm and the transformation from 2D to 3D. The analysis further requires an R package called "RSEE". For more information: https://www.tau.ac.il/~ilan99/see/index.htm

Figure S3. High tangential speed indicates movement on the floor from Vertical exploration and dimensional modularity in mice

Figure S3. High tangential speed (Vθ) is only observed in segments of movement on the ground. Therefore, capturing the boundary between the arena floor and the wall using the mouse's smoothed two-dimensional tracking coordinates is enabled by using only the set of points where Vθ was high. The left panel presents the smoothed 2D coordinates of a selected mouse (V02) during the entire session. In the middle panel, only points where Vθ≥8 cm/s (75th percentile) were plotted. In the left panel, only points where Vθ≥32 cm/s (92nd percentile) were plotted. Green marks the calculated boundary between the floor and the wall using the modified arena builder algorithm

Figure S4. Percentile-LOESS function estimates the growth in ascents' height from Vertical exploration and dimensional modularity in mice

Figure S4. Capturing the dynamics of growth using a 90th percentile-LOESS function, illustrated by the maximal height per ascent in a selected mouse (first 64 ascents). Scaled raw data of maximal height per ascent are coloured in grey and the percentile-LOESS function is coloured in red. The dashed black horizontal line represents the 80% threshold, and the orange vertical line represents the time (in ascents) to reach the 80% threshold. The dynamics of growth in height consist roughly of two stages - a stage of rearing episodes (ascents 1 to 32), followed by rapid growth in height, until eventually the mouse reaches the top of the wall

Figure S5. Estimating the number of direction changes in an ascent from Vertical exploration and dimensional modularity in mice

Figure S5. Illustration of the method for isolating 90-degrees and 180-degrees turns in a single selected ascent, in order to count direction changes. A) The original path traced on the wall during ascent 182 of mouse V07. The directionality of the movement within the ascent is marked by a transition from yellow (ascent starts) to red (ascent ends). B) The movement is constrained to either only vertical or only horizontal, by reducing the lower respective speed to zero and reconstructing the path. C) Noise reduction by repeated moving average (two repetitions with window width of 1.6 seconds). D) Repetition of the step presented in panel B using the smoothed coordinates. The estimate for the number of direction changes is the number of 90-degrees and 180-degrees turns in the path presented in panel D (in this example 34)

Figure S2. Example for a behavioural trap in which the mouse "gets stuck" on the wall from Vertical exploration and dimensional modularity in mice

Figure S2. The first full blown ascent (in red) performed by mouse V05 is exceptionally long relative to subsequent ascents (in black), as though this mouse "gets trapped" on the wall. In mouse V05, the most extreme example of the phenomenon, the exceptional ascent lasted 3 minutes and 54 seconds, which is more than twice as long as the second longest ascent (1:46 minutes), and considerably longer than subsequent ascents reaching the top of the wire mesh (approx. 30 seconds each). This ascent is wide and involves a high number of pivots and direction changes, which usually characterize ascents performed in a late stage of the build-up in width and complexity