Positioning of pyrimidine motifs around cassette exons defines their PTB-dependent splicing in Arabidopsis.

Alternative splicing (AS) is a complex process that generates transcript variants from a single pre-mRNA and is involved in numerous biological functions. Many RNA-binding proteins are known to regulate AS; however, little is known about the underlying mechanisms, especially outside the mammalian clade. Here, we show that polypyrimidine tract binding proteins (PTBs) from Arabidopsis thaliana regulate AS of cassette exons via pyrimidine (Py)-rich motifs close to the alternative splice sites. Mutational studies on three PTB-dependent cassette exon events revealed that only some of the Py motifs in this region are critical for AS. Moreover, in vitro binding of PTBs did not reflect a motif's impact on AS in vivo. Our mutational studies and bioinformatic investigation of all known PTB-regulated cassette exons from A. thaliana and human suggested that the binding position of PTBs relative to a cassette exon defines whether its inclusion or skipping is induced. Accordingly, exon skipping is associated with a higher frequency of Py stretches within the cassette exon, and in human also upstream of it, whereas exon inclusion is characterized by increased Py motif occurrence downstream of said exon. Enrichment of Py motifs downstream of PTB-activated 5' splice sites is also seen for PTB-dependent intron removal and alternative 5' splice site events from A. thaliana, suggesting this is a common step of exon definition. In conclusion, the position-dependent AS regulatory mechanism by PTB homologs has been conserved during the separate evolution of plants and mammals, while other critical features, in particular intron length, have considerably changed.

A transient in planta editing assay identifies specific binding of the splicing regulator PTB as a prerequisite for cassette exon inclusion.

The dynamic interaction of RNA-binding proteins (RBPs) with their target RNAs contributes to the diversity of ribonucleoprotein (RNP) complexes that are involved in a myriad of biological processes. Identifying the RNP components at high resolution and defining their interactions are key to understanding their regulation and function. Expressing fusions between an RBP of interest and an RNA editing enzyme can result in nucleobase changes in target RNAs, representing a recent addition to experimental approaches for profiling RBP/RNA interactions. Here, we have used the MS2 protein/RNA interaction to test four RNA editing proteins for their suitability to detect target RNAs of RBPs in planta. We have established a transient test system for fast and simple quantification of editing events and identified the hyperactive version of the catalytic domain of an adenosine deaminase (hADARcd) as the most suitable editing enzyme. Examining fusions between homologs of polypyrimidine tract binding proteins (PTBs) from Arabidopsis thaliana and hADARcd allowed determining target RNAs with high sensitivity and specificity. Moreover, almost complete editing of a splicing intermediate provided insight into the order of splicing reactions and PTB dependency of this particular splicing event. Addition of sequences for nuclear localisation of the fusion protein increased the editing efficiency, highlighting this approach's potential to identify RBP targets in a compartment-specific manner. Our studies have established the editing-based analysis of interactions between RBPs and their RNA targets in a fast and straightforward assay, offering a new system to study the intricate composition and functions of plant RNPs in vivo.

The influence of electrode-tissue-coverage on RF lesion formation and local impedance: Insights from an ex vivo model.

BACKGROUND: The influence of power, duration and contact force (CF) on radiofrequency (RF) lesion formation is well known, whereas data on local impedance (LI) and electrode-tissue-coverage (ETC) is scarce. The objective was to investigate their effect on lesion formation in an ex vivo model. METHODS AND RESULTS: An ex vivo model was developed utilizing cross-sections of porcine heart preparations and a force-sensing, LI-measuring catheter. N = 72 lesion were created systematically varying ETC (minor/full), CF (1-5 g, 10-15 g, 20-25 g) and power (20 W, 30 W, 40 W, 50 W). In minor ETC, the distal tip of the catheter was in electric contact with the tissue, in full ETC the whole catheter tip was embedded within the tissue. Lesion size and all parameters were measured once per second (n = 3320). LI correlated strongly with lesion depth (r = -0.742 for ΔLI; r = 0.781 for %LI-drop). Lesions in full ETC were significantly wider and deeper compared to minor ETC (p < .001) and steam pops were more likely. Baseline LI, ΔLI, and %LI-drop were significantly higher in full ETC (p < .001). In lesions resulting in steam pops, baseline LI, and ΔLI were significantly higher. The influence of CF on lesion size was higher in minor ETC than in full ETC. CONCLUSIONS: ETC is a main determinant of lesion size and occurrence of steam pops. Baseline LI and LI-drop are useful surrogate parameters for real-time assessment of ETC and ΔLI correlates strongly with lesion size.

SNF1-RELATED KINASE 1 and TARGET OF RAPAMYCIN control light-responsive splicing events and developmental characteristics in etiolated Arabidopsis seedlings.

The kinases SNF1-RELATED KINASE 1 (SnRK1) and TARGET OF RAPAMYCIN (TOR) are central sensors of the energy status, linking this information via diverse regulatory mechanisms to plant development and stress responses. Despite the well-studied functions of SnRK1 and TOR under conditions of limited or ample energy availability, respectively, little is known about the extent to which the 2 sensor systems function and how they are integrated in the same molecular process or physiological context. Here, we demonstrate that both SnRK1 and TOR are required for proper skotomorphogenesis in etiolated Arabidopsis (Arabidopsis thaliana) seedlings, light-induced cotyledon opening, and regular development in light. Furthermore, we identify SnRK1 and TOR as signaling components acting upstream of light- and sugar-regulated alternative splicing events, expanding the known action spectra for these 2 key players in energy signaling. Our findings imply that concurring SnRK1 and TOR activities are required throughout various phases of plant development. Based on the current knowledge and our findings, we hypothesize that turning points in the activities of these sensor kinases, as expected to occur upon illumination of etiolated seedlings, instead of signaling thresholds reflecting the nutritional status may modulate developmental programs in response to altered energy availability.

3D-2D Distance Maps Conversion Enhances Classification of Craniosynostosis.

OBJECTIVE: Diagnosis of craniosynostosis using photogrammetric 3D surface scans is a promising radiation-free alternative to traditional computed tomography. We propose a 3D surface scan to 2D distance map conversion enabling the usage of the first convolutional neural networks (CNNs)-based classification of craniosynostosis. Benefits of using 2D images include preserving patient anonymity, enabling data augmentation during training, and a strong under-sampling of the 3D surface with good classification performance. METHODS: The proposed distance maps sample 2D images from 3D surface scans using a coordinate transformation, ray casting, and distance extraction. We introduce a CNN-based classification pipeline and compare our classifier to alternative approaches on a dataset of 496 patients. We investigate into low-resolution sampling, data augmentation, and attribution mapping. RESULTS: Resnet18 outperformed alternative classifiers on our dataset with an F1-score of 0.964 and an accuracy of 98.4%. Data augmentation on 2D distance maps increased performance for all classifiers. Under-sampling allowed 256-fold computation reduction during ray casting while retaining an F1-score of 0.92. Attribution maps showed high amplitudes on the frontal head. CONCLUSION: We demonstrated a versatile mapping approach to extract a 2D distance map from the 3D head geometry increasing classification performance, enabling data augmentation during training on 2D distance maps, and the usage of CNNs. We found that low-resolution images were sufficient for a good classification performance. SIGNIFICANCE: Photogrammetric surface scans are a suitable craniosynostosis diagnosis tool for clinical practice. Domain transfer to computed tomography seems likely and can further contribute to reducing ionizing radiation exposure for infants.

The Impact of Standard Ablation Strategies for Atrial Fibrillation on Cardiovascular Performance in a Four-Chamber Heart Model.

PURPOSE: Atrial fibrillation is one of the most frequent cardiac arrhythmias in the industrialized world and ablation therapy is the method of choice for many patients. However, ablation scars alter the electrophysiological activation and the mechanical behavior of the affected atria. Different ablation strategies with the aim to terminate atrial fibrillation and prevent its recurrence exist but their impact on the performance of the heart is often neglected. METHODS: In this work, we present a simulation study analyzing five commonly used ablation scar patterns and their combinations in the left atrium regarding their impact on the pumping function of the heart using an electromechanical whole-heart model. We analyzed how the altered atrial activation and increased stiffness due to the ablation scars affect atrial as well as ventricular contraction and relaxation. RESULTS: We found that systolic and diastolic function of the left atrium is impaired by ablation scars and that the reduction of atrial stroke volume of up to 11.43% depends linearly on the amount of inactivated tissue. Consequently, the end-diastolic volume of the left ventricle, and thus stroke volume, was reduced by up to 1.4 and 1.8%, respectively. During ventricular systole, left atrial pressure was increased by up to 20% due to changes in the atrial activation sequence and the stiffening of scar tissue. CONCLUSION: This study provides biomechanical evidence that atrial ablation has acute effects not only on atrial contraction but also on ventricular performance. Therefore, the position and extent of ablation scars is not only important for the termination of arrhythmias but is also determining long-term pumping efficiency. If confirmed in larger cohorts, these results have the potential to help tailoring ablation strategies towards minimal global cardiovascular impairment.

On cheap entropy-sparsified regression learning.

Regression learning is one of the long-standing problems in statistics, machine learning, and deep learning (DL). We show that writing this problem as a probabilistic expectation over (unknown) feature probabilities - thus increasing the number of unknown parameters and seemingly making the problem more complex-actually leads to its simplification, and allows incorporating the physical principle of entropy maximization. It helps decompose a very general setting of this learning problem (including discretization, feature selection, and learning multiple piece-wise linear regressions) into an iterative sequence of simple substeps, which are either analytically solvable or cheaply computable through an efficient second-order numerical solver with a sublinear cost scaling. This leads to the computationally cheap and robust non-DL second-order Sparse Probabilistic Approximation for Regression Task Analysis (SPARTAn) algorithm, that can be efficiently applied to problems with millions of feature dimensions on a commodity laptop, when the state-of-the-art learning tools would require supercomputers. SPARTAn is compared to a range of commonly used regression learning tools on synthetic problems and on the prediction of the El Niño Southern Oscillation, the dominant interannual mode of tropical climate variability. The obtained SPARTAn learners provide more predictive, sparse, and physically explainable data descriptions, clearly discerning the important role of ocean temperature variability at the thermocline in the equatorial Pacific. SPARTAn provides an easily interpretable description of the timescales by which these thermocline temperature features evolve and eventually express at the surface, thereby enabling enhanced predictability of the key drivers of the interannual climate.

Impact of data synthesis strategies for the classification of craniosynostosis.

Introduction: Photogrammetric surface scans provide a radiation-free option to assess and classify craniosynostosis. Due to the low prevalence of craniosynostosis and high patient restrictions, clinical data are rare. Synthetic data could support or even replace clinical data for the classification of craniosynostosis, but this has never been studied systematically. Methods: We tested the combinations of three different synthetic data sources: a statistical shape model (SSM), a generative adversarial network (GAN), and image-based principal component analysis for a convolutional neural network (CNN)-based classification of craniosynostosis. The CNN is trained only on synthetic data but is validated and tested on clinical data. Results: The combination of an SSM and a GAN achieved an accuracy of 0.960 and an F1 score of 0.928 on the unseen test set. The difference to training on clinical data was smaller than 0.01. Including a second image modality improved classification performance for all data sources. Conclusions: Without a single clinical training sample, a CNN was able to classify head deformities with similar accuracy as if it was trained on clinical data. Using multiple data sources was key for a good classification based on synthetic data alone. Synthetic data might play an important future role in the assessment of craniosynostosis.

CNN-Based Classification of Craniosynostosis Using 2D Distance Maps.

Craniosynostosis is a condition associated with the premature fusion of skull sutures affecting infants. 3D photogrammetric scans are a promising alternative to computed tomography scans in cases of single suture or nonsyndromic synostosis for diagnostic imaging, but oftentimes diagnosis is not automated and relies on additional cephalometric measure-ments and the experience of the surgeon. We propose an alternative representation of the infant's head shape created from 3D photogrammetric surface scans as 2D distance maps. Those 2D distance maps rely on ray casting to extract distances from a center point to the head surface, arranging them into a 2D image grid. We use the distance map for an original convolutional neural network (CNN)-based classification approach, which is evaluated on a publicly available synthetic dataset for benchmarking and also tested on clinical data. Qualitative differences of different head shapes can be ob-served in the distance maps. The CNN-based classifier achieves accuracies of 100 % on the publicly available synthetic dataset and 98.86 % on the clinical test set. Our distance map approach demonstrates the diagnostic value of 3D photogrammetry and the possibility of automatic, CNN-based diagnosis. Future steps include the improvement of the mapping method and testing the CNN on more pathologies.

A Radiation-Free Classification Pipeline for Craniosynostosis Using Statistical Shape Modeling.

BACKGROUND: Craniosynostosis is a condition caused by the premature fusion of skull sutures, leading to irregular growth patterns of the head. Three-dimensional photogrammetry is a radiation-free alternative to the diagnosis using computed tomography. While statistical shape models have been proposed to quantify head shape, no shape-model-based classification approach has been presented yet. METHODS: We present a classification pipeline that enables an automated diagnosis of three types of craniosynostosis. The pipeline is based on a statistical shape model built from photogrammetric surface scans. We made the model and pathology-specific submodels publicly available, making it the first publicly available craniosynostosis-related head model, as well as the first focusing on infants younger than 1.5 years. To the best of our knowledge, we performed the largest classification study for craniosynostosis to date. RESULTS: Our classification approach yields an accuracy of 97.8 %, comparable to other state-of-the-art methods using both computed tomography scans and stereophotogrammetry. Regarding the statistical shape model, we demonstrate that our model performs similar to other statistical shape models of the human head. CONCLUSION: We present a state-of-the-art shape-model-based classification approach for a radiation-free diagnosis of craniosynostosis. Our publicly available shape model enables the assessment of craniosynostosis on realistic and synthetic data.

A high-resolution single-molecule sequencing-based Arabidopsis transcriptome using novel methods of Iso-seq analysis.

BACKGROUND: Accurate and comprehensive annotation of transcript sequences is essential for transcript quantification and differential gene and transcript expression analysis. Single-molecule long-read sequencing technologies provide improved integrity of transcript structures including alternative splicing, and transcription start and polyadenylation sites. However, accuracy is significantly affected by sequencing errors, mRNA degradation, or incomplete cDNA synthesis. RESULTS: We present a new and comprehensive Arabidopsis thaliana Reference Transcript Dataset 3 (AtRTD3). AtRTD3 contains over 169,000 transcripts-twice that of the best current Arabidopsis transcriptome and including over 1500 novel genes. Seventy-eight percent of transcripts are from Iso-seq with accurately defined splice junctions and transcription start and end sites. We develop novel methods to determine splice junctions and transcription start and end sites accurately. Mismatch profiles around splice junctions provide a powerful feature to distinguish correct splice junctions and remove false splice junctions. Stratified approaches identify high-confidence transcription start and end sites and remove fragmentary transcripts due to degradation. AtRTD3 is a major improvement over existing transcriptomes as demonstrated by analysis of an Arabidopsis cold response RNA-seq time-series. AtRTD3 provides higher resolution of transcript expression profiling and identifies cold-induced differential transcription start and polyadenylation site usage. CONCLUSIONS: AtRTD3 is the most comprehensive Arabidopsis transcriptome currently. It improves the precision of differential gene and transcript expression, differential alternative splicing, and transcription start/end site usage analysis from RNA-seq data. The novel methods for identifying accurate splice junctions and transcription start/end sites are widely applicable and will improve single-molecule sequencing analysis from any species.

Simulation-Based Estimation of the Number of Cameras Required for 3D Reconstruction in a Narrow-Baseline Multi-Camera Setup.

Graphical visualization systems are a common clinical tool for displaying digital images and three-dimensional volumetric data. These systems provide a broad spectrum of information to support physicians in their clinical routine. For example, the field of radiology enjoys unrestricted options for interaction with the data, since information is pre-recorded and available entirely in digital form. However, some fields, such as microsurgery, do not benefit from this yet. Microscopes, endoscopes, and laparoscopes show the surgical site as it is. To allow free data manipulation and information fusion, 3D digitization of surgical sites is required. We aimed to find the number of cameras needed to add this functionality to surgical microscopes. For this, we performed in silico simulations of the 3D reconstruction of representative models of microsurgical sites with different numbers of cameras in narrow-baseline setups. Our results show that eight independent camera views are preferable, while at least four are necessary for a digital surgical site. In most cases, eight cameras allow the reconstruction of over 99% of the visible part. With four cameras, still over 95% can be achieved. This answers one of the key questions for the development of a prototype microscope. In future, such a system can provide functionality which is unattainable today.

3D-Guided Face Manipulation of 2D Images for the Prediction of Post-Operative Outcome After Cranio-Maxillofacial Surgery.

Cranio-maxillofacial surgery often alters the aesthetics of the face which can be a heavy burden for patients to decide whether or not to undergo surgery. Today, physicians can predict the post-operative face using surgery planning tools to support the patient's decision-making. While these planning tools allow a simulation of the post-operative face, the facial texture must usually be captured by another 3D texture scan and subsequently mapped on the simulated face. This approach often results in face predictions that do not appear realistic or lively looking and are therefore ill-suited to guide the patient's decision-making. Instead, we propose a method using a generative adversarial network to modify a facial image according to a 3D soft-tissue estimation of the post-operative face. To circumvent the lack of available data pairs between pre- and post-operative measurements we propose a semi-supervised training strategy using cycle losses that only requires paired open-source data of images and 3D surfaces of the face's shape. After training on "in-the-wild" images we show that our model can realistically manipulate local regions of a face in a 2D image based on a modified 3D shape. We then test our model on four clinical examples where we predict the post-operative face according to a 3D soft-tissue prediction of surgery outcome, which was simulated by a surgery planning tool. As a result, we aim to demonstrate the potential of our approach to predict realistic post-operative images of faces without the need of paired clinical data, physical models, or 3D texture scans.

To move or not to move: roles and specificity of plant RNA mobility.

Intercellular communication in plants coordinates cellular functions during growth and development, and in response to environmental cues. RNAs figure prominently among the mobile signaling molecules used. Many hundreds of RNA species move over short and long distances, and can be mutually exchanged in biotic interactions. Understanding the specificity determinants of RNA mobility and the physiological relevance of this phenomenon are areas of active research. Here, we highlight the recent progress in our knowledge of small RNA and messenger RNA movement. Particular emphasis is given to novel insight into the specificity determinants of messenger RNA mobility, the role of small RNA movement in development, and the specificity of RNA exchange in plant-plant and plant-microbe interactions.

Multifactorial and Species-Specific Feedback Regulation of the RNA Surveillance Pathway Nonsense-Mediated Decay in Plants.

Nonsense-mediated decay (NMD) is an RNA surveillance mechanism that detects aberrant transcript features and triggers degradation of erroneous as well as physiological RNAs. Originally considered to be constitutive, NMD is now recognized to be tightly controlled in response to inherent signals and diverse stresses. To gain a better understanding of NMD regulation and its functional implications, we systematically examined feedback control of the central NMD components in two dicot and one monocot species. On the basis of the analysis of transcript features, turnover rates and steady-state levels, up-frameshift (UPF) 1, UPF3 and suppressor of morphological defects on genitalia (SMG) 7, but not UPF2, are under feedback control in both dicots. In the monocot investigated in this study, only SMG7 was slightly induced upon NMD inhibition. The detection of the endogenous NMD factor proteins in Arabidopsis thaliana substantiated a negative correlation between NMD activity and SMG7 amounts. Furthermore, evidence was provided that SMG7 is required for the dephosphorylation of UPF1. Our comprehensive and comparative study of NMD feedback control in plants reveals complex and species-specific attenuation of this RNA surveillance pathway, with critical implications for the numerous functions of NMD in physiology and stress responses.

NMD-Based Gene Regulation-A Strategy for Fitness Enhancement in Plants?

Post-transcriptional RNA quality control is a vital issue for all eukaryotes to secure accurate gene expression, both on a qualitative and quantitative level. Among the different mechanisms, nonsense-mediated mRNA decay (NMD) is an essential surveillance system that triggers degradation of both aberrant and physiological transcripts. By targeting a substantial fraction of all transcripts for degradation, including many alternative splicing variants, NMD has a major impact on shaping transcriptomes. Recent progress on the transcriptome-wide profiling and physiological analyses of NMD-deficient plant mutants revealed crucial roles for NMD in gene regulation and environmental responses. In this review, we will briefly summarize our current knowledge of the recognition and degradation of NMD targets, followed by an account of NMD's regulation and physiological functions. We will specifically discuss plant-specific aspects of RNA quality control and its functional contribution to the fitness and environmental responses of plants.

Electrocardiographic Imaging Using a Spatio-Temporal Basis of Body Surface Potentials-Application to Atrial Ectopic Activity.

Electrocardiographic imaging (ECGI) strongly relies on a priori assumptions and additional information to overcome ill-posedness. The major challenge of obtaining good reconstructions consists in finding ways to add information that effectively restricts the solution space without violating properties of the sought solution. In this work, we attempt to address this problem by constructing a spatio-temporal basis of body surface potentials (BSP) from simulations of many focal excitations. Measured BSPs are projected onto this basis and reconstructions are expressed as linear combinations of corresponding transmembrane voltage (TMV) basis vectors. The novel method was applied to simulations of 100 atrial ectopic foci with three different conduction velocities. Three signal-to-noise ratios (SNR) and bases of six different temporal lengths were considered. Reconstruction quality was evaluated using the spatial correlation coefficient of TMVs as well as estimated local activation times (LAT). The focus localization error was assessed by computing the geodesic distance between true and reconstructed foci. Compared with an optimally parameterized Tikhonov-Greensite method, the BSP basis reconstruction increased the mean TMV correlation by up to 22, 24, and 32% for an SNR of 40, 20, and 0 dB, respectively. Mean LAT correlation could be improved by up to 5, 7, and 19% for the three SNRs. For 0 dB, the average localization error could be halved from 15.8 to 7.9 mm. For the largest basis length, the localization error was always below 34 mm. In conclusion, the new method improved reconstructions of atrial ectopic activity especially for low SNRs. Localization of ectopic foci turned out to be more robust and more accurate. Preliminary experiments indicate that the basis generalizes to some extent from the training data and may even be applied for reconstruction of non-ectopic activity.

Subcellular Compartmentation of Alternatively Spliced Transcripts Defines SERINE/ARGININE-RICH PROTEIN30 Expression.

Alternative splicing (AS) is prevalent in higher eukaryotes, and generation of different AS variants is tightly regulated. Widespread AS occurs in response to altered light conditions and plays a critical role in seedling photomorphogenesis, but despite its frequency and effect on plant development, the functional role of AS remains unknown for most splicing variants. Here, we characterized the light-dependent AS variants of the gene encoding the splicing regulator Ser/Arg-rich protein SR30 in Arabidopsis (Arabidopsis thaliana). We demonstrated that the splicing variant SR30.2, which is predominantly produced in darkness, is enriched within the nucleus and strongly depleted from ribosomes. Light-induced AS from a downstream 3' splice site gives rise to SR30.1, which is exported to the cytosol and translated, coinciding with SR30 protein accumulation upon seedling illumination. Constitutive expression of SR30.1 and SR30.2 fused to fluorescent proteins revealed their identical subcellular localization in the nucleoplasm and nuclear speckles. Furthermore, expression of either variant shifted splicing of a genomic SR30 reporter toward SR30.2, suggesting that an autoregulatory feedback loop affects SR30 splicing. We provide evidence that SR30.2 can be further spliced and, unlike SR30.2, the resulting cassette exon variant SR30.3 is sensitive to nonsense-mediated decay. Our work delivers insight into the complex and compartmentalized RNA processing mechanisms that control the expression of the splicing regulator SR30 in a light-dependent manner.

A Novel Application for Low Frequency Electrochemical Impedance Spectroscopy as an Online Process Monitoring Tool for Viable Cell Concentrations.

New approaches in process monitoring during industrial fermentations are not only limited to classical pH, dO2 and offgas analysis, but use different in situ and online sensors based on different physical principles to determine biomass, product quality, lysis and far more. One of the very important approaches is the in situ accessibility of viable cell concentration (VCC). This knowledge provides increased efficiency in monitoring and controlling strategies during cultivations. Electrochemical impedance spectroscopy-EIS-is used to monitor biomass in a fermentation of E. coli BL21(DE3), producing a recombinant protein using a fed batch-based approach. Increases in the double layer capacitance (Cdl), determined at frequencies below 1 kHz, are proportional to the increase of biomass in the batch and fed batch phase, monitored in offline and online modes for different cultivations. A good correlation of Cdl with cell density is found and in order to get an appropriate verification of this method, different state-of-the-art biomass measurements are performed and compared. Since measurements in this frequency range are largely determined by the double layer region between the electrode and media, rather minor interferences with process parameters (aeration, stirring) are to be expected. It is shown that impedance spectroscopy at low frequencies is a powerful tool for cultivation monitoring.

Alternative Splicing Substantially Diversifies the Transcriptome during Early Photomorphogenesis and Correlates with the Energy Availability in Arabidopsis.

Plants use light as source of energy and information to detect diurnal rhythms and seasonal changes. Sensing changing light conditions is critical to adjust plant metabolism and to initiate developmental transitions. Here, we analyzed transcriptome-wide alterations in gene expression and alternative splicing (AS) of etiolated seedlings undergoing photomorphogenesis upon exposure to blue, red, or white light. Our analysis revealed massive transcriptome reprogramming as reflected by differential expression of ∼20% of all genes and changes in several hundred AS events. For more than 60% of all regulated AS events, light promoted the production of a presumably protein-coding variant at the expense of an mRNA with nonsense-mediated decay-triggering features. Accordingly, AS of the putative splicing factor REDUCED RED-LIGHT RESPONSES IN CRY1CRY2 BACKGROUND1, previously identified as a red light signaling component, was shifted to the functional variant under light. Downstream analyses of candidate AS events pointed at a role of photoreceptor signaling only in monochromatic but not in white light. Furthermore, we demonstrated similar AS changes upon light exposure and exogenous sugar supply, with a critical involvement of kinase signaling. We propose that AS is an integration point of signaling pathways that sense and transmit information regarding the energy availability in plants.