Motivation

Translation initiation is a key step in the regulation of gene expression. In addition to the annotated translation initiation sites (TISs), the translation process may also start at multiple alternative TISs (including both AUG and non-AUG codons), which makes it challenging to predict TISs and study the underlying regulatory mechanisms. Meanwhile, the advent of several high-throughput sequencing techniques for profiling initiating ribosomes at single-nucleotide resolution, e.g. GTI-seq and QTI-seq, provides abundant data for systematically studying the general principles of translation initiation and the development of computational method for TIS identification.

Methods

We have developed a deep learning-based framework, named TITER, for accurately predicting TISs on a genome-wide scale based on QTI-seq data. TITER extracts the sequence features of translation initiation from the surrounding sequence contexts of TISs using a hybrid neural network and further integrates the prior preference of TIS codon composition into a unified prediction framework.

Results

Extensive tests demonstrated that TITER can greatly outperform the state-of-the-art prediction methods in identifying TISs. In addition, TITER was able to identify important sequence signatures for individual types of TIS codons, including a Kozak-sequence-like motif for AUG start codon. Furthermore, the TITER prediction score can be related to the strength of translation initiation in various biological scenarios, including the repressive effect of the upstream open reading frames on gene expression and the mutational effects influencing translation initiation efficiency.

Availability and implementation

TITER is available as an open-source software and can be downloaded from https://github.com/zhangsaithu/titer .

Contact

lzhang20@mail.tsinghua.edu.cn or zengjy321@tsinghua.edu.cn.

Supplementary information

Supplementary data are available at Bioinformatics online.

Pseudouridine (Ψ) is the most prevalent post-transcriptional RNA modification and is widespread in small cellular RNAs and mRNAs. However, the functions, mechanisms, and precise distribution of Ψs (especially in mRNAs) still remain largely unclear. The landscape of Ψs across the transcriptome has not yet been fully delineated. Here, we present a highly effective model based on a convolutional neural network (CNN), called PseudoUridyLation Site Estimator (PULSE), to analyze large-scale profiling data of Ψ sites and characterize the contextual sequence features of pseudouridylation. PULSE, consisting of two alternatively-stacked convolution and pooling layers followed by a fully-connected neural network, can automatically learn the hidden patterns of pseudouridylation from the local sequence information. Extensive validation tests demonstrated that PULSE can outperform other state-of-the-art prediction methods and achieve high prediction accuracy, thus enabling us to further characterize the transcriptome-wide landscape of Ψ sites. We further showed that the prediction results derived from PULSE can provide novel insights into understanding the functional roles of pseudouridylation, such as the regulations of RNA secondary structure, codon usage, translation, and RNA stability, and the connection to single nucleotide variants. The source code and final model for PULSE are available at https://github.com/mlcb-thu/PULSE.

Characterizing the binding behaviors of RNA-binding proteins (RBPs) is important for understanding their functional roles in gene expression regulation. However, current high-throughput experimental methods for identifying RBP targets, such as CLIP-seq and RNAcompete, usually suffer from the false negative issue. Here, we develop a deep boosting based machine learning approach, called DeBooster, to accurately model the binding sequence preferences and identify the corresponding binding targets of RBPs from CLIP-seq data. Comprehensive validation tests have shown that DeBooster can outperform other state-of-the-art approaches in RBP target prediction. In addition, we have demonstrated that DeBooster may provide new insights into understanding the regulatory functions of RBPs, including the binding effects of the RNA helicase MOV10 on mRNA degradation, the potentially different ADAR1 binding behaviors related to its editing activity, as well as the antagonizing effect of RBP binding on miRNA repression. Moreover, DeBooster may provide an effective index to investigate the effect of pathogenic mutations in RBP binding sites, especially those related to splicing events. We expect that DeBooster will be widely applied to analyze large-scale CLIP-seq experimental data and can provide a practically useful tool for novel biological discoveries in understanding the regulatory mechanisms of RBPs. The source code of DeBooster can be downloaded from http://github.com/dongfanghong/deepboost.

The unicellular heterotrophic thraustochytrids are attractive candidates for commercial polyunsaturated fatty acids (PUFA) production. However, the reactive oxygen species (ROS) generated in their aerobic fermentation process often limits their PUFA titer. Yet, the specific mechanisms of ROS involvement in the crosstalk between oxidative stress and intracellular lipid synthesis remain poorly described. Metabolic engineering to improve the PUFA yield in thraustochytrids without compromising growth is an important aspect of economic feasibility. To fill this gap, we overexpressed the antioxidative gene superoxide dismutase (SOD1) by integrating it into the genome of thraustochytrid Schizochytrium sp. PKU#Mn4 using a novel genetic transformation system. This study reports the ROS alleviation, enhanced PUFA production and transcriptome changes resulting from the SOD1 overexpression. SOD1 activity in the recombinant improved by 5.2-71.6% along with 7.8-38.5% decline in ROS during the fermentation process. Interestingly, the total antioxidant capacity in the recombinant remained higher than wild-type and above zero in the entire process. Although lipid profile was similar to that of wild-type, the concentrations of major fatty acids in the recombinant were significantly (p ≤ 0.05) higher. The PUFA titer increased up to 1232 ± 41 mg/L, which was 32.9% higher (p ≤ 0.001) than the wild type. Transcriptome analysis revealed strong downregulation of genes potentially involved in β-oxidation of fatty acids in peroxisome and upregulation of genes catalyzing lipid biosynthesis. Our results enrich the knowledge on stress-induced PUFA biosynthesis and the putative role of ROS in the regulation of lipid metabolism in oleaginous thraustochytrids. This study provides a new and alternate strategy for cost-effective industrial fermentation of PUFA.

Retinopathy of prematurity (ROP) is one of the leading causes of childhood visual impairment and blindness. However, there are still very few effective pharmacological interventions for ROP. Histone deacetylase 6 (HDAC6)-mediated disassembly of photoreceptor cilia has recently been implicated as an early event in the pathogenesis of ROP. Herein it is shown that enhanced expression of HDAC6 by intravitreal injection of adenoviruses encoding HDAC6 induces the typical pathological changes associated with ROP in mice, including disruption of the membranous disks of photoreceptor outer segments and a decrease in electroretinographic amplitudes. Hdac6 transgenic mice exhibit similar ROP-related defects in retinal structures and functions and disassembly of photoreceptor cilia, whereas Hdac6 knockout mice are resistant to oxygen change-induced retinal defects. It is further shown that blocking HDAC6-mediated cilium disassembly by intravitreal injection of small-molecule compounds protect mice from ROP-associated retinal defects. The findings indicate that pharmacological targeting of the HDAC6-cilium axis may represent a promising strategy for the prevention of ROP.

AbstractCongenital heart diseases (CHD) are a class of birth defects affecting ∼1% of live births. These conditions are hallmarked by extreme genetic heterogeneity, and therefore, despite a strong genetic component, only a very handful of at-risk loci in CHD have been identified. We herein introduced systems analyses to uncover the hidden organization on biological networks of genomic mutations in CHD, and leveraged network analysis techniques to integrate the human interactome, large-scale patient exomes, the fetal heart spatial transcriptomes, and single-cell transcriptomes of clinical samples. We identified a highly connected network in CHD where most of the member proteins had previously uncharacterized functions in regulating fetal heart development. While genes on the network displayed strong enrichment for heart-specific functions, a sub-group, active specifically at early developmental stages, also regulates fetal brain development, thereby providing mechanistic insights into the clinical comorbidities between CHD and neurodevelopmental conditions. At a small scale, we experimentally verified previously uncharacterized cardiac functions of several novel proteins employing cellular assays and gene editing techniques. At a global scale, our study revealed developmental dynamics of the identified CHD network and observed the strongest enrichment for pathogenic mutations in the network specific to hypoplastic left heart syndrome (HLHS). Our single-cell transcriptome analysis further identified pervasive dysregulation of the network in cardiac endothelial cells and the conduction system in the HLHS left ventricle. Taken together, our systems analyses identified novel factors in CHD, revealed key molecular mechanisms in HLHS, and provides a generalizable framework readily applicable to studying many other complex diseases.

Despite a strong genetic component, only a few genes have been identified in congenital heart diseases (CHDs). We introduced systems analyses to uncover the hidden organization on biological networks of mutations in CHDs and leveraged network analysis to integrate the protein interactome, patient exomes, and single-cell transcriptomes of the developing heart. We identified a CHD network regulating heart development and observed that a sub-network also regulates fetal brain development, thereby providing mechanistic insights into the clinical comorbidities between CHDs and neurodevelopmental conditions. At a small scale, we experimentally verified uncharacterized cardiac functions of several proteins. At a global scale, our study revealed developmental dynamics of the network and observed its association with the hypoplastic left heart syndrome (HLHS), which was further supported by the dysregulation of the network in HLHS endothelial cells. Overall, our work identified previously uncharacterized CHD factors and provided a generalizable framework applicable to studying many other complex diseases. A record of this paper's Transparent Peer Review process is included in the supplemental information.

Novel phenothiazine-dithiocarbamate analogues were designed by molecular hybridization strategy and synthesized and evaluated for their anticancer activity in vitro against three selected cancer cell lines (EC-109, MGC-803, and PC-3). The preliminary structure-activity relationship (SAR) for this phenothiazine-dithiocarbamate hybrids is explored. Among all analogues, 2-oxo-2-(10H-phenothiazin-10-yl)ethyl 4-ethylpiperazine-1-carbodithioate (8a) showed the most potent inhibitory activity with an [Formula: see text] value of [Formula: see text] against PC-3 cells. In addition, compound 8a could arrest the cell cycle at the G1 phase and regulate the expression of G1 checkpoint-related proteins, suggesting that phenothiazine-dithiocarbamate hybrids might be useful as cell cycle blockers.

A series of 5,6-diaryl-1,2,4-triazines hybrids bearing a 1,2,3-triazole linker were synthesized by molecular hybridization strategy and evaluated for antiproliferative activity against three selected cancer cell lines (MGC-803, EC-109 and PC-3). The first structure-activity relationship (SAR) for these 5,6-diaryl-1,2,4-triazines is explored in this report with evaluation of 15 variants of the structural class. Among these chemical derivatives, 3-(((1-(4-fluorobenzyl)-1H-1,2,3-triazol-4-yl)methyl)thio)-5,6-diphenyl-1,2,4-triazine (11E) showed the more potent inhibitory effect against three cell lines than 5-Fu. Cellular mechanism studies in MGC-803 cells elucidated 11E inhibited colony formation and arrested cell cycle at G2/M phase. Furthermore, compound 11E caused morphological changes, decreased mitochondrial membrane potential, and induced apoptosis through the apoptosis-related proteins in MGC-803 cells. It was the first time, to our knowledge, that 5,6-diaryl-1,2,4-triazines bearing a 1,2,3-triazole linker were used as potential apoptosis inducers.