A critical role of RBM8a in proliferation and differentiation of embryonic neural progenitors

BACKGROUND: Nonsense mediated mRNA decay (NMD) is an RNA surveillance mechanism that controls RNA stability and ensures the speedy degradation of erroneous and unnecessary transcripts. This mechanism depends on several core factors in the exon junction complex (EJC), eIF4A3, RBM8a, Magoh, and BTZ, as well as peripheral factors to distinguish premature stop codons (PTCs) from normal stop codons in transcripts. Recently, emerging evidence has indicated that NMD factors are associated with neurodevelopmental disorders such as autism spectrum disorder (ASD) and intellectual disability (ID). However, the mechanism in which these factors control embryonic brain development is not clear. RESULT: We found that RBM8a is critical for proliferation and differentiation in cortical neural progenitor cells (NPCs). RBM8a is highly expressed in the subventricular zone (SVZ) of the early embryonic cortex, suggesting that RBM8a may play a role in regulating NPCs. RBM8a overexpression stimulates embryonic NPC proliferation and suppresses neuronal differentiation. Conversely, knockdown of RBM8a in the neocortex reduces NPC proliferation and promotes premature neuronal differentiation. Moreover, overexpression of RBM8a suppresses cell cycle exit and keeps cortical NPCs in a proliferative state. To uncover the underlying mechanisms of this phenotype, genome-wide RNAseq was used to identify potential downstream genes of RBM8a in the brain, which have been implicated in autism and neurodevelopmental disorders. Interestingly, autism and schizophrenia risk genes are highly represented in downstream transcripts of RBM8a. In addition, RBM8a regulates multiple alternative splicing genes and NMD targets that are implicated in ASD. Taken together, this data suggests a novel role of RBM8a in the regulation of neurodevelopment. CONCLUSIONS: Our studies provide some insight into causes of mental illnesses and will facilitate the development of new therapeutic strategies for neurodevelopmental illnesses. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13064-015-0045-7) contains supplementary material, which is available to authorized users

A Multibranch Deep Neural Network for the Superresolution of Solar Magnetograms

The existing superresolution (SR) models for solar magnetograms are mostly borrowed from the SR models for natural images. They are less effective for processing solar magnetograms with a very large dynamic range and very rich image features. In this paper, a multibranch superresolution (MBSR) model is specially designed for solar magnetograms. First, we split a low-resolution magnetogram into a group of overlapping image patches, and classify them into three categories according to magnetic flux intensity, namely simple, medium, and complex. Then, image patches of each category are fed into the corresponding branch of the MBSR network, the lightweight branch for simple image patches and the heavyweight one for complex image patches. The advantage of such a strategy is twofold. On the one hand, active regions are allocated more computational resources to train a heavyweight branch more fully, while quiet regions are allocated fewer computational resources to train a lightweight branch for saving computational resources. On the other hand, a lightweight network with a simple nonlinear function is preferable to simple regions, while a heavyweight one may be underfitting. Additionally, to verify the effectiveness of the proposed model, a magnetic field structure similarity metric is proposed to measure the artifacts of the generated high-resolution (HR) magnetograms. Experimental results show that the proposed MBSR model generates HR magnetograms highly consistent with the HMI ones, and achieves the best performance over five objective metrics, including peak signal-to-noise ratio and structure similarity, etc

Super-resolution of Solar Magnetograms Using Deep Learning

Abstract Currently, data-driven models of solar activity forecast are investigated extensively by using machine learning. For model training, it is highly demanded to establish a large database which may contain observations coming from different instruments with different spatio-temporal resolutions. In this paper, we employ deep learning models for super-resolution (SR) of magnetogram of Michelson Doppler Imager (MDI) in order to achieve the same spatial resolution of Helioseismic and Magnetic Imager (HMI). First, a generative adversarial network (GAN) is designed to transfer characteristics of MDI onto downscaled HMI, getting low-resolution HMI magnetogram in the same domain as MDI. Then, with the paired low-resolution and high-resolution HMI magnetograms, another GAN is trained in a supervised learning way, which consists of two streams, one is for generating high-fidelity image content, the other is explicitly optimized for generating elaborate image gradients. Thus, these two streams work together to guarantee both high-fidelity and photorealistic super-resolved images. Experimental results demonstrate that the proposed method can generate super-resolved magnetograms with perceptual-pleasant visual quality. Meanwhile, the best PSNR, LPIPS, RMSE, comparable SSIM and CC are obtained by the proposed method. The source code and data set can be accessed via https://github.com/filterbank/SPSR.</jats:p

Enhanced tolerance to drought stress resulting from Caragana korshinskii CkWRKY33 in transgenic Arabidopsis thaliana

Abstract Background It is well known that WRKY transcription factors play important roles in plant growth and development, defense regulation and stress responses. Results In this study, a WRKY transcription factor, WRKY33, was cloned from Caragana korshinskii. A sequence structure analysis showed that it belonged to the Group-I type. Subcellular localization experiments in tobacco epidermal cells showed the presence of CkWRKY33 in the nucleus. Additionally, CkWRKY33 was overexpressed in Arabidopsis thaliana. A phenotypic investigation revealed that compared with wild-type plants, CkWRKY33-overexpressing transgenic plants had higher survival rates, as well as relative soluble sugar, proline and peroxidase contents, but lower malondialdehyde contents, following a drought stress treatment. Conclusions This suggested that the overexpression of CkWRKY33 led to an enhanced drought-stress tolerance in transgenic A. thaliana. Thus, CkWRKY33 may act as a positive regulator involved in the drought-stress responses in Caragana korshinskii. </jats:sec

Enhanced Tolerance to Drought Stress Resulting from Caragana Korshinskii CkWRKY33 in Transgenic Arabidopsis Thaliana

Abstract Background: It is well known that WRKY transcription factors play important roles in plant growth and development, defense regulation and stress responses.Results: In this study, a WRKY transcription factor, WRKY33, was cloned from Caragana korshinskii. A sequence structure analysis showed that it belonged to the Group-I type. Subcellular localization experiments in tobacco epidermal cells showed the presence of CkWRKY33 in the nucleus. Additionally, CkWRKY33 was overexpressed in Arabidopsis thaliana. A phenotypic investigation revealed that compared with wild-type plants CkWRKY33-overexpressing transgenic plants had higher survival rates, as well as relative water, soluble sugar, proline and peroxidase contents, but lower malondialdehyde contents, following a drought stress treatment. Conclusions: This suggested that the overexpression of CkWRKY33 led to an enhanced drought-stress tolerance in transgenic A. thaliana. Thus, CkWRKY33 may act as a positive regulator involved in the drought-stress responses in Caragana korshinskii.</jats:p

Enhanced tolerance to drought stress resulting from Caragana korshinskii CkWRKY33 in transgenic Arabidopsis thaliana

Abstract Background: It is well known that WRKY transcription factors play important roles in plant growth and development, defense regulation and stress responses.Results: In this study, a WRKY transcription factor, WRKY33, was cloned from Caragana korshinskii. A sequence structure analysis showed that it belonged to the Group-I type. Subcellular localization experiments in tobacco epidermal cells showed the presence of CkWRKY33 in the nucleus. Additionally, CkWRKY33 was overexpressed in Arabidopsis thaliana. A phenotypic investigation revealed that compared with wild-type plants CkWRKY33-overexpressing transgenic plants had higher survival rates, as well as relative water, soluble sugar, proline and peroxidase contents, but lower malondialdehyde contents, following a drought stress treatment.Conclusions: This suggested that the overexpression of CkWRKY33 led to an enhanced drought-stress tolerance in transgenic A. thaliana. Thus, CkWRKY33 may act as a positive regulator involved in the drought-stress responses in Caragana korshinskii.</jats:p

Deletion of CTNNB1 in inhibitory circuitry contributes to autism-associated behavioral defects

Mutations in β-catenin (CTNNB1) have been implicated in cancer and mental disorders. Recently, loss-of-function mutations of CTNNB1 were linked to intellectual disability (ID), and rare mutations were identified in patients with autism spectrum disorder (ASD). As a key regulator of the canonical Wnt pathway, CTNNB1 plays an essential role in neurodevelopment. However, the function of CTNNB1 in specific neuronal subtypes is unclear. To understand how CTNNB1 deficiency contributes to ASD, we generated CTNNB1 conditional knockout (cKO) mice in parvalbumin interneurons. The cKO mice had increased anxiety, but had no overall change in motor function. Interestingly, CTNNB1 cKO in PV-interneurons significantly impaired object recognition and social interactions and elevated repetitive behaviors, which mimic the core symptoms of patients with ASD. Surprisingly, deleting CTNNB1 in parvalbumin-interneurons enhanced spatial memory. To determine the effect of CTNNB1 KO in overall neuronal activity, we found that c-Fos was significantly reduced in the cortex, but not in the dentate gyrus and the amygdala. Our findings revealed a cell type-specific role of CTNNB1 gene in regulation of cognitive and autistic-like behaviors. Thus, this study has important implications for development of therapies for ASDs carrying the CTNNB1 mutation or other ASDs that are associated with mutations in the Wnt pathway. In addition, our study contributes to a broader understanding of the regulation of the inhibitory circuitry

Potential metabolic and genetic interaction among viruses, methanogen and methanotrophic archaea, and their syntrophic partners

AbstractThe metabolism of methane in anoxic ecosystems is mainly mediated by methanogens and methane-oxidizing archaea (MMA), key players in global carbon cycling. Viruses are vital in regulating their host fate and ecological function. However, our knowledge about the distribution and diversity of MMA viruses and their interactions with hosts is rather limited. Here, by searching metagenomes containing mcrA (the gene coding for the α-subunit of methyl-coenzyme M reductase) from a wide variety of environments, 140 viral operational taxonomic units (vOTUs) that potentially infect methanogens or methane-oxidizing archaea were retrieved. Four MMA vOTUs (three infecting the order Methanobacteriales and one infecting the order Methanococcales) were predicted to cross-domain infect sulfate-reducing bacteria. By facilitating assimilatory sulfur reduction, MMA viruses may increase the fitness of their hosts in sulfate-depleted anoxic ecosystems and benefit from synthesis of the sulfur-containing amino acid cysteine. Moreover, cell-cell aggregation promoted by MMA viruses may be beneficial for both the viruses and their hosts by improving infectivity and environmental stress resistance, respectively. Our results suggest a potential role of viruses in the ecological and environmental adaptation of methanogens and methane-oxidizing archaea.</jats:p