Carbon Nanotubes Connecting and Encapsulating MoS2-Doped SnO2 Nanoparticles as an Excellent Lithium Storage Performance Anode Material.

Doping and carbon encapsulation modifications have been proven to be effective methods for enhancing the lithium storage performance of batteries. The hydrothermal method and ball milling are commonly used methods for material synthesis. In this study, a composite anode material rich in carbon nanotubes (CNTs) conductive tubular network connection and encapsulation of SnO2-MoS2@CNTs (SMC) was synthesized by combining these two methods. In this highly conductive network, nano-SnO2 particles are uniformly dispersed and embedded in MoS2 with a layered structure, and the obtained SnO2-MoS2 composite material is tightly connected and encapsulated by the tubular network of CNTs. It is worth noting that the incorporation of layered MoS2 not only effectively anchors the SnO2 nanoparticles, but also provides a broader space for lithium-ion movement due to the larger interlayer spacing. The conductive network of CNTs shortens the diffusion path of electrons and Li+ and provides more diffusion channels. The reversible capacity of the SnO2-MoS2@CNTs nanocomposite material remains at 1069.3 mA h g-1 after 320 cycles at 0.2 A g-1, and it exhibits excellent long-term cycling stability, maintaining 904.5 mA h g-1 after 1000 cycles at 1.0 A g-1. The composite material demonstrates excellent pseudocapacitive contribution rate performance, with a contribution rate of 87% at 2.0 mV s-1. The results indicate that SnO2-MoS2@CNTs has excellent electrochemical lithium storage performance and is a promising anode material for lithium-ion batteries.

Traditional Chinese medicine constitution and sarcopenia: a cross-sectional study.

Objective: Sarcopenia is a gradually advancing systemic disorder affecting skeletal muscles, primarily distinguished by diminished muscle mass and functional decline. As of present, a universally accepted diagnostic criterion for sarcopenia has yet to be established. From the perspective of the constitution theory in traditional Chinese medicine (TCM), the Yin-deficiency constitution is believed to have a significant correlation with the development of sarcopenia. The primary objective of this study was to examine the potential association between sarcopenia and Yin-deficiency constitution. Methods: The present study is a cross-sectional analysis. The Asian Working Group for Sarcopenia (AWGS) recommended a diagnostic criterion for sarcopenia. A total of 141 participants over 50 years of age were diagnosed with sarcopenia. To determine the constitution of each patient, classification and determination standards were used in traditional Chinese medicine. In this study, a combination of logistic regression and propensity score matching (PSM) was employed to analyze a dataset comprising 1,372 eligible observations. The diagnostic efficacy of the test in distinguishing sarcopenia was assessed through receiver operating characteristic (ROC) curve analysis. Results: The relationship between Yin-deficiency constitution and sarcopenia was examined using logistic regression analysis. In the crude model, the odds ratio (OR) was found to be 3.20 (95% confidence interval [CI]: 1.70-6.03). After adjusting for various confounding factors, including gender, sex, 6 m walking test/(m/s), SMI, and maximum grip strength/kg, the OR increased to 9.70 (95% CI: 3.20-69.38). The associations between seven other biased traditional Chinese medicine (TCM) constitutions and sarcopenia were not found to be statistically significant in the fully adjusted model. The propensity score matching (PSM) analysis yielded consistent results with the logistic regression analysis. Receiver operating characteristic (ROC) curve analysis showed that the AUC of the Yin-deficiency constitution combined with age and gender reached 0.707. Conclusion: Among the nine TCM constitutions examined, the Yin-deficiency constitution demonstrates an independent association with sarcopenia. Yin-deficiency constitution may serve as a potential risk factor for the development of sarcopenia. To establish a causal relationship, further experimental investigations are warranted. The diagnostic performance of sarcopenia is effectively demonstrated by the Yin-deficiency constitution combined with age and gender.

The original scores of traditional Chinese medicine constitutions are risk and diagnostic factors in middle-aged and older adults with sarcopenia.

Objective: Sarcopenia is a geriatric syndrome that occurs with age and is characterized by a gradual decline in muscle mass, power, and functionality. It serves as a prominent contributor to frailty, disability, and mortality among older individuals. Currently, no standardized global guidelines exist for the diagnosis of sarcopenia. This study aimed to establish the correlation between sarcopenia and the constitutions of traditional Chinese medicine (TCM), considering the connection between physical functioning and sarcopenia. Methods: A total of 1441 participants in this study were diagnosed with sarcopenia. The Asian Working Group for Sarcopenia (AWGS) proposed a sarcopenia definition algorithm. To determine the constitution of each participant, classification and determination standards were used in traditional Chinese medicine. This study evaluated the demographics, lifestyles, and self-reported medical history of individuals diagnosed with sarcopenia through a self-administered questionnaire. The constitution of the participants was determined using TCM classification and determination standards. Subsequently, we analyzed the results of univariate analysis and multivariate regression and constructed a receiver operating characteristic (ROC) curve. Results: Participants who were diagnosed with sarcopenia had substantially lower original Neutral constitution scores (P < 0.050). In comparison to those without sarcopenia, individuals with sarcopenia exhibited notably elevated original Qi-deficiency, Yang-deficiency, Yin-deficiency, Blood-stagnation, and Qi-stagnation scores in contrast to those in the healthy group (P < 0.050). The identified risk factors associated with sarcopenia included the following: Neutral (OR = 0.903), Qi-deficiency (in males, OR = 1.126), Yang-deficiency (OR = 1.062), Phlegm-dampness (in males, OR = 0.833), and Blood-stagnation (in females, OR = 1.089). The highest area under the curve (AUC) was observed for the original neutral constitution score, followed by the Yang-deficiency and blood-stagnation scores (0.644, 0.613, and 0.611, respectively). Additionally, the AUC for the combined original scores of all nine constitutions among males reached 0.778. Conclusions: In this cross-sectional study of older people with higher original Qi-deficiency, Yin deficiency, Yang-deficiency, Blood-stagnation, and Qi-stagnation were associated with sarcopenia. Notably, various TCM constitutions are significantly linked to sarcopenia. There was a significant occurrence of various body constitution types among individuals diagnosed with sarcopenia. The mixture of the nine original constitution scores exhibited good diagnostic performance for sarcopenia in males.

An Energy-Efficient ECG Processor with Ultra-Low-Parameter Multi-Stage Neural Network and Optimized Power-of-Two Quantization.

This work presents an energy-efficient ECG processor designed for Cardiac Arrhythmia Classification. The processor integrates a pre-processing and neural network accelerator, achieved through algorithm-hardware co-design to optimize hardware resources. We propose a lightweight two-stage neural network architecture, where the first stage includes discrete wavelet transformation and an ultra-low-parameter multilayer perceptron (MLP) network, and the second stage utilizes group convolution and channel shuffle. Both stages leverage neural networks for hardware resource reuse and feature a reconfigurable processing element array and memory blocks adapted to the proposed two-stage structure to efficiently handle various convolution and MLP layers operations in the two-stage network. Additionally, an optimized power-of-two (OPOT) quantization technique is proposed to enhance accuracy in low-bit quantization, and a multiplier-less processing element structure tailored for the OPOT weight quantization is introduced. The ECG processor was implemented on a 65nm CMOS process technology with 4KB of SRAM memory, achieving an energy consumption per interference of 0.15 uJ with a power supply of 1V, 64% energy saving compared to the recent state-of-the-art work. Under 4-bit weight precision, the 5-class ECG signal classification accuracy reached 98.59% on the MIT-BIH arrhythmia dataset.

A genome-wide spectrum of tandem repeat expansions in 338,963 humans.

The Genome Aggregation Database (gnomAD), widely recognized as the gold-standard reference map of human genetic variation, has largely overlooked tandem repeat (TR) expansions, despite the fact that TRs constitute ∼6% of our genome and are linked to over 50 human diseases. Here, we introduce the TR-gnomAD (https://wlcb.oit.uci.edu/TRgnomAD), a biobank-scale reference of 0.86 million TRs derived from 338,963 whole-genome sequencing (WGS) samples of diverse ancestries (39.5% non-European samples). TR-gnomAD offers critical insights into ancestry-specific disease prevalence using disparities in TR unit number frequencies among ancestries. Moreover, TR-gnomAD is able to differentiate between common, presumably benign TR expansions, which are prevalent in TR-gnomAD, from those potentially pathogenic TR expansions, which are found more frequently in disease groups than within TR-gnomAD. Together, TR-gnomAD is an invaluable resource for researchers and physicians to interpret TR expansions in individuals with genetic diseases.

Gut microbiota profiling in obese children from Southeastern China.

Childhood obesity not only has a negative impact on a child's health but is also a significant risk factor for adult obesity and related metabolic disorders, making it a major global public health concern. Recent studies have revealed the crucial role of gut microbiota in the occurrence and development of obesity, in addition to genetic and lifestyle factors. In this study, we recruited 19 normal-weight children and 47 children with varying degrees of obesity. A questionnaire survey was conducted to inquire about the family background, lifestyle habits and dietary composition of the 66 children. Findings indicate that fathers of obese children tend to be obese themselves, while children with highly educated mothers are more likely to maintain a normal weight. Furthermore, overweight children tend to spend more time on electronic devices and less time on physical activities compared to their normal-weight counterparts. Obese children exhibit significant differences in breakfast and dinner dietary composition when compared to children with normal weight. Additionally, the gut microbiota of these 66 children was analyzed using 16S rRNA sequencing. Analysis of gut microbiota composition showed similar compositions among children with varying degrees of obesity, but significant differences were observed in comparison to normal-weight children. Obese children exhibited a reduced proportion of Bacteroidota and an increased proportion of Firmicutes, resulting in an elevated Firmicutes/Bacteroidota ratio. Moreover, Actinobacteriota were found to be increased in the gut microbiota of children with varying degrees of obesity. PICRUSt analysis indicated significant metabolic differences in the microbiota functions between obese and normal-weight children, suggesting the composition of gut microbiota could be a crucial factor contributing to obesity. These findings provide valuable insights for the treatment of childhood obesity.

vizAPA: visualizing dynamics of alternative polyadenylation from bulk and single-cell data.

MOTIVATION: Alternative polyadenylation (APA) is a widespread post-transcriptional regulatory mechanism across all eukaryotes. With the accumulation of genome-wide APA sites, especially those with single-cell resolution, it is imperative to develop easy-to-use visualization tools to guide APA analysis. RESULTS: We developed an R package called vizAPA for visualizing APA dynamics from bulk and single-cell data. vizAPA implements unified data structures for APA data and genome annotations. vizAPA also enables identification of genes with differential APA usage across biological samples and/or cell types. vizAPA provides four unique modules for extensively visualizing APA dynamics across biological samples and at the single-cell level. vizAPA could serve as a plugin in many routine APA analysis pipelines to augment studies for APA dynamics. AVAILABILITY AND IMPLEMENTATION: https://github.com/BMILAB/vizAPA.

TDP-43 dysregulation of polyadenylation site selection is a defining feature of RNA misprocessing in ALS/FTD and related disorders.

Nuclear clearance and cytoplasmic aggregation of the RNA-binding protein TDP-43 are observed in many neurodegenerative disorders, including amyotrophic lateral sclerosis (ALS) and fronto- temporal dementia (FTD). Although TDP-43 dysregulation of splicing has emerged as a key event in these diseases, TDP-43 can also regulate polyadenylation; yet, this has not been adequately studied. Here, we applied the dynamic analysis of polyadenylation from RNA-seq (DaPars) tool to ALS/FTD transcriptome datasets, and report extensive alternative polyadenylation (APA) upon TDP-43 alteration in ALS/FTD cell models and postmortem ALS/FTD neuronal nuclei. Importantly, many identified APA genes highlight pathways implicated in ALS/FTD pathogenesis. To determine the functional significance of APA elicited by TDP-43 nuclear depletion, we examined microtubule affinity regulating kinase 3 (MARK3). Nuclear loss of TDP-43 yielded increased expression of MARK3 transcripts with longer 3'UTRs, resulting in greater transcript stability and elevated MARK3 protein levels, which promotes increased neuronal tau S262 phosphorylation. Our findings define changes in polyadenylation site selection as a previously unrecognized feature of TDP-43-driven disease pathology in ALS/FTD and highlight a potentially novel mechanistic link between TDP-43 dysfunction and tau regulation.

Spectral Clustering Community Detection Algorithm Based on Point-Wise Mutual Information Graph Kernel.

To address the problem that traditional spectral clustering algorithms cannot obtain the complete structural information of networks, this paper proposes a spectral clustering community detection algorithm, PMIK-SC, based on the point-wise mutual information (PMI) graph kernel. The kernel is constructed according to the point-wise mutual information between nodes, which is then used as a proximity matrix to reconstruct the network and obtain the symmetric normalized Laplacian matrix. Finally, the network is partitioned by the eigendecomposition and eigenvector clustering of the Laplacian matrix. In addition, to determine the number of clusters during spectral clustering, this paper proposes a fast algorithm, BI-CNE, for estimating the number of communities. For a specific network, the algorithm first reconstructs the original network and then runs Monte Carlo sampling to estimate the number of communities by Bayesian inference. Experimental results show that the detection speed and accuracy of the algorithm are superior to other existing algorithms for estimating the number of communities. On this basis, the spectral clustering community detection algorithm PMIK-SC also has high accuracy and stability compared with other community detection algorithms and spectral clustering algorithms.

MEDIPIPE: an automated and comprehensive pipeline for cfMeDIP-seq data quality control and analysis.

SUMMARY: Cell-free methylated DNA immunoprecipitation and high-throughput sequencing (cfMeDIP-seq) has emerged as a promising liquid biopsy technology to detect cancers and monitor treatments. While several bioinformatics tools for DNA methylation analysis have been adapted for cfMeDIP-seq data, an end-to-end pipeline and quality control framework specifically for this data type is still lacking. Here, we present the MEDIPIPE, which provides a one-stop solution for cfMeDIP-seq data quality control, methylation quantification, and sample aggregation. The major advantages of MEDIPIPE are: (i) ease of implementation and reproducibility with Snakemake containerized execution environments that will be automatically deployed via Conda; (ii) flexibility to handle different experimental settings with a single configuration file; and (iii) computationally efficiency for large-scale cfMeDIP-seq profiling data analysis and aggregation. AVAILABILITY AND IMPLEMENTATION: This pipeline is an open-source software under the MIT license and it is freely available at https://github.com/pughlab/MEDIPIPE.

Machine and deep learning-based clinical characteristics and laboratory markers for the prediction of sarcopenia.

BACKGROUND: Sarcopenia is an age-related progressive skeletal muscle disorder involving the loss of muscle mass or strength and physiological function. Efficient and precise AI algorithms may play a significant role in the diagnosis of sarcopenia. In this study, we aimed to develop a machine learning model for sarcopenia diagnosis using clinical characteristics and laboratory indicators of aging cohorts. METHODS: We developed models of sarcopenia using the baseline data from the West China Health and Aging Trend (WCHAT) study. For external validation, we used the Xiamen Aging Trend (XMAT) cohort. We compared the support vector machine (SVM), random forest (RF), eXtreme Gradient Boosting (XGB), and Wide and Deep (W&D) models. The area under the receiver operating curve (AUC) and accuracy (ACC) were used to evaluate the diagnostic efficiency of the models. RESULTS: The WCHAT cohort, which included a total of 4057 participants for the training and testing datasets, and the XMAT cohort, which consisted of 553 participants for the external validation dataset, were enrolled in this study. Among the four models, W&D had the best performance (AUC = 0.916 ± 0.006, ACC = 0.882 ± 0.006), followed by SVM (AUC =0.907 ± 0.004, ACC = 0.877 ± 0.006), XGB (AUC = 0.877 ± 0.005, ACC = 0.868 ± 0.005), and RF (AUC = 0.843 ± 0.031, ACC = 0.836 ± 0.024) in the training dataset. Meanwhile, in the testing dataset, the diagnostic efficiency of the models from large to small was W&D (AUC = 0.881, ACC = 0.862), XGB (AUC = 0.858, ACC = 0.861), RF (AUC = 0.843, ACC = 0.836), and SVM (AUC = 0.829, ACC = 0.857). In the external validation dataset, the performance of W&D (AUC = 0.970, ACC = 0.911) was the best among the four models, followed by RF (AUC = 0.830, ACC = 0.769), SVM (AUC = 0.766, ACC = 0.738), and XGB (AUC = 0.722, ACC = 0.749). CONCLUSIONS: The W&D model not only had excellent diagnostic performance for sarcopenia but also showed good economic efficiency and timeliness. It could be widely used in primary health care institutions or developing areas with an aging population. TRIAL REGISTRATION: Chictr.org, ChiCTR 1800018895.

Alternative 3'-untranslated regions regulate high-salt tolerance of Spartina alterniflora.

High-salt stress continues to challenge the growth and survival of many plants. Alternative polyadenylation (APA) produces mRNAs with different 3'-untranslated regions (3' UTRs) to regulate gene expression at the post-transcriptional level. However, the roles of alternative 3' UTRs in response to salt stress remain elusive. Here, we report the function of alternative 3' UTRs in response to high-salt stress in S. alterniflora (Spartina alterniflora), a monocotyledonous halophyte tolerant of high-salt environments. We found that high-salt stress induced global APA dynamics, and ∼42% of APA genes responded to salt stress. High-salt stress led to 3' UTR lengthening of 207 transcripts through increasing the usage of distal poly(A) sites. Transcripts with alternative 3' UTRs were mainly enriched in salt stress-related ion transporters. Alternative 3' UTRs of HIGH-AFFINITY K+ TRANSPORTER 1 (SaHKT1) increased RNA stability and protein synthesis in vivo. Regulatory AU-rich elements were identified in alternative 3' UTRs, boosting the protein level of SaHKT1. RNAi-knock-down experiments revealed that the biogenesis of 3' UTR lengthening in SaHKT1 was controlled by the poly(A) factor CLEAVAGE AND POLYADENYLATION SPECIFICITY FACTOR 30 (SaCPSF30). Over-expression of SaHKT1 with an alternative 3' UTR in rice (Oryza sativa) protoplasts increased mRNA accumulation of salt-tolerance genes in an AU-rich element-dependent manner. These results suggest that mRNA 3' UTR lengthening is a potential mechanism in response to high-salt stress. These results also reveal complex regulatory roles of alternative 3' UTRs coupling APA and regulatory elements at the post-transcriptional level in plants.

A Survey on Methods for Predicting Polyadenylation Sites from DNA Sequences, Bulk RNA-seq, and Single-cell RNA-seq.

Alternative polyadenylation (APA) plays important roles in modulating mRNA stability, translation, and subcellular localization, and contributes extensively to shaping eukaryotic transcriptome complexity and proteome diversity. Identification of poly(A) sites (pAs) on a genome-wide scale is a critical step toward understanding the underlying mechanism of APA-mediated gene regulation. A number of established computational tools have been proposed to predict pAs from diverse genomic data. Here we provided an exhaustive overview of computational approaches for predicting pAs from DNA sequences, bulk RNA sequencing (RNA-seq) data, and single-cell RNA sequencing (scRNA-seq) data. Particularly, we examined several representative tools using bulk RNA-seq and scRNA-seq data from peripheral blood mononuclear cells and put forward operable suggestions on how to assess the reliability of pAs predicted by different tools. We also proposed practical guidelines on choosing appropriate methods applicable to diverse scenarios. Moreover, we discussed in depth the challenges in improving the performance of pA prediction and benchmarking different methods. Additionally, we highlighted outstanding challenges and opportunities using new machine learning and integrative multi-omics techniques, and provided our perspective on how computational methodologies might evolve in the future for non-3' untranslated region, tissue-specific, cross-species, and single-cell pA prediction.

The cell-free DNA methylome captures distinctions between localized and metastatic prostate tumors.

Metastatic prostate cancer remains a major clinical challenge and metastatic lesions are highly heterogeneous and difficult to biopsy. Liquid biopsy provides opportunities to gain insights into the underlying biology. Here, using the highly sensitive enrichment-based sequencing technology, we provide analysis of 60 and 175 plasma DNA methylomes from patients with localized and metastatic prostate cancer, respectively. We show that the cell-free DNA methylome can capture variations beyond the tumor. A global hypermethylation in metastatic samples is observed, coupled with hypomethylation in the pericentromeric regions. Hypermethylation at the promoter of a glucocorticoid receptor gene NR3C1 is associated with a decreased immune signature. The cell-free DNA methylome is reflective of clinical outcomes and can distinguish different disease types with 0.989 prediction accuracy. Finally, we show the ability of predicting copy number alterations from the data, providing opportunities for joint genetic and epigenetic analysis on limited biological samples.

The 5-Hydroxymethylcytosine Landscape of Prostate Cancer.

Analysis of DNA methylation is a valuable tool to understand disease progression and is increasingly being used to create diagnostic and prognostic clinical biomarkers. While conversion of cytosine to 5-methylcytosine (5mC) commonly results in transcriptional repression, further conversion to 5-hydroxymethylcytosine (5hmC) is associated with transcriptional activation. Here we perform the first study integrating whole-genome 5hmC with DNA, 5mC, and transcriptome sequencing in clinical samples of benign, localized, and advanced prostate cancer. 5hmC is shown to mark activation of cancer drivers and downstream targets. Furthermore, 5hmC sequencing revealed profoundly altered cell states throughout the disease course, characterized by increased proliferation, oncogenic signaling, dedifferentiation, and lineage plasticity to neuroendocrine and gastrointestinal lineages. Finally, 5hmC sequencing of cell-free DNA from patients with metastatic disease proved useful as a prognostic biomarker able to identify an aggressive subtype of prostate cancer using the genes TOP2A and EZH2, previously only detectable by transcriptomic analysis of solid tumor biopsies. Overall, these findings reveal that 5hmC marks epigenomic activation in prostate cancer and identify hallmarks of prostate cancer progression with potential as biomarkers of aggressive disease. SIGNIFICANCE: In prostate cancer, 5-hydroxymethylcytosine delineates oncogene activation and stage-specific cell states and can be analyzed in liquid biopsies to detect cancer phenotypes. See related article by Wu and Attard, p. 3880.

Neuroprotective Effects of Estrogen Through BDNF-Transient Receptor Potential Channels 6 Signaling Pathway in the Hippocampus in a Rat Model of Perimenopausal Depression.

Estradiol (E2) has been proven to be effective in treating perimenopausal depression (PD); however, the downstream signaling pathways have not been fully elucidated. Transient receptor potential channels 6 (TRPC6) plays a vital role in promoting neuronal development and the formation of excitatory synapses. At present, we found that the serum levels of E2 and brain-derived neurotrophic factor (BDNF) declined significantly in the women with PD compared to perimenopausal women, which was accompanied by a clear reduction in TRPC6 levels. To further reveal the effects of TRPC6 on neuronal survival and excitability, the PD-like rat model was established by the total removal of left ovary and 80% removal of right ovary followed by 21 days of the chronic unpredictable mild stress. Intragastric administration of E2 (2 mg/kg), intraperitoneal injection of BDNF/TrB signaling pathway inhibitor (K252a, 100 µg/kg) and TRPC6 agonist (OAG, 0.6 mg/kg), and intracerebroventricular infusion of anti-BDNF antibody for blocking BDNF (0.5 µg/24 µl/rat) daily for 21 days were conducted. The levels of BDNF and TRPC6 in rat serum were lower in PD rats compared to the control rats; the depression-like behavior was induced, the neuronal death rate in the hippocampus increased, and the thickness of postsynaptic density (PSD) and the number of asymmetric synapses decreased significantly in the PD group. E2 treatment greatly upregulated the serum levels of BDNF and TRPC6, the neuronal excitability indicated by an elevation in the PSD thickness and the numbers of asymmetric synapses, and these actions were reversed by K252a; co-administration of TRPC6 agonist and K252a improved neuronal degeneration and increased the neuronal excitability induced in the E2-treated PD rats. K252a or anti-BDNF antibody inhibited the increased neuronal BDNF and TRPC6 expression in E2-treated PD rats; co-treatment of TRPC6 agonist and anti-BDNF antibody reduced neuronal death and increased the BDNF and TRPC6 expression in the hippocampal CA1 neurons in the E2-treated PD rats. These results suggest that the neuroprotective role of E2 in PD is closely related to enhance the activity of BDNF/TRPC6 pathway and is helpful to provide new prevention and strategies.

scAPAdb: a comprehensive database of alternative polyadenylation at single-cell resolution.

Alternative polyadenylation (APA) is a widespread regulatory mechanism of transcript diversification in eukaryotes, which is increasingly recognized as an important layer for eukaryotic gene expression. Recent studies based on single-cell RNA-seq (scRNA-seq) have revealed cell-to-cell heterogeneity in APA usage and APA dynamics across different cell types in various tissues, biological processes and diseases. However, currently available APA databases were all collected from bulk 3'-seq and/or RNA-seq data, and no existing database has provided APA information at single-cell resolution. Here, we present a user-friendly database called scAPAdb (http://www.bmibig.cn/scAPAdb), which provides a comprehensive and manually curated atlas of poly(A) sites, APA events and poly(A) signals at the single-cell level. Currently, scAPAdb collects APA information from > 360 scRNA-seq experiments, covering six species including human, mouse and several other plant species. scAPAdb also provides batch download of data, and users can query the database through a variety of keywords such as gene identifier, gene function and accession number. scAPAdb would be a valuable and extendable resource for the study of cell-to-cell heterogeneity in APA isoform usages and APA-mediated gene regulation at the single-cell level under diverse cell types, tissues and species.

SPOP mutation induces DNA methylation via stabilizing GLP/G9a.

Mutations in SPOP E3 ligase gene are reportedly associated with genome-wide DNA hypermethylation in prostate cancer (PCa) although the underlying mechanisms remain elusive. Here, we demonstrate that SPOP binds and promotes polyubiquitination and degradation of histone methyltransferase and DNMT interactor GLP. SPOP mutation induces stabilization of GLP and its partner protein G9a and aberrant upregulation of global DNA hypermethylation in cultured PCa cells and primary PCa specimens. Genome-wide DNA methylome analysis shows that a subset of tumor suppressor genes (TSGs) including FOXO3, GATA5, and NDRG1, are hypermethylated and downregulated in SPOP-mutated PCa cells. DNA methylation inhibitor 5-azacytidine effectively reverses expression of the TSGs examined, inhibits SPOP-mutated PCa cell growth in vitro and in mice, and enhances docetaxel anti-cancer efficacy. Our findings reveal the GLP/G9a-DNMT module as a mediator of DNA hypermethylation in SPOP-mutated PCa. They suggest that SPOP mutation could be a biomarker for effective treatment of PCa with DNA methylation inhibitor alone or in combination with taxane chemotherapeutics.

QuantifyPoly(A): reshaping alternative polyadenylation landscapes of eukaryotes with weighted density peak clustering.

The dynamic choice of different polyadenylation sites in a gene is referred to as alternative polyadenylation, which functions in many important biological processes. Large-scale messenger RNA 3' end sequencing has revealed that cleavage sites for polyadenylation are presented with microheterogeneity. To date, the conventional determination of polyadenylation site clusters is subjective and arbitrary, leading to inaccurate annotations. Here, we present a weighted density peak clustering method, QuantifyPoly(A), to accurately quantify genome-wide polyadenylation choices. Applying QuantifyPoly(A) on published 3' end sequencing datasets from both animals and plants, their polyadenylation profiles are reshaped into myriads of novel polyadenylation site clusters. Most of these novel polyadenylation site clusters show significantly dynamic usage across different biological samples or associate with binding sites of trans-acting factors. Upstream sequences of these clusters are enriched with polyadenylation signals UGUA, UAAA and/or AAUAAA in a species-dependent manner. Polyadenylation site clusters also exhibit species specificity, while plants ones generally show higher microheterogeneity than that of animals. QuantifyPoly(A) is broadly applicable to any types of 3' end sequencing data and species for accurate quantification and construction of the complex and dynamic polyadenylation landscape and enables us to decode alternative polyadenylation events invisible to conventional methods at a much higher resolution.