Dual roles of the Arabidopsis PEAT complex in histone H2A deubiquitination and H4K5 acetylation.

Histone H2A monoubiquitination is associated with transcriptional repression and needs to be removed by deubiquitinases to facilitate gene transcription in eukaryotes. However, the deubiquitinase responsible for genome-wide H2A deubiquitination in plants has yet to be identified. In this study, we found that the previously identified PWWP-EPCR-ARID-TRB (PEAT) complex components interact with both the ubiquitin-specific protease UBP5 and the redundant histone acetyltransferases HAM1 and HAM2 (HAM1/2) to form a larger version of PEAT complex in Arabidopsis thaliana. UBP5 functions as an H2A deubiquitinase in a nucleosome substrate-dependent manner in vitro and mediates H2A deubiquitination at the whole-genome level in vivo. HAM1/2 are shared subunits of the PEAT complex and the conserved NuA4 histone acetyltransferase complex, and are responsible for histone H4K5 acetylation. Within the PEAT complex, the PWWP components (PWWP1, PWWP2, and PWWP3) directly interact with UBP5 and are necessary for UBP5-mediated H2A deubiquitination, while the EPCR components (EPCR1 and EPCR2) directly interact with HAM1/2 and are required for HAM1/2-mediated H4K5 acetylation. Collectively, our study not only identifies dual roles of the PEAT complex in H2A deubiquitination and H4K5 acetylation but also illustrates how these processes collaborate at the whole-genome level to regulate the transcription and development in plants.

WRKY transcription factors and OBERON histone-binding proteins form complexes to balance plant growth and stress tolerance.

WRKY transcription factors in plants are known to be able to mediate either transcriptional activation or repression, but the mechanism regulating their transcriptional activity is largely unclear. We found that group IId WRKY transcription factors interact with OBERON (OBE) proteins, forming redundant WRKY-OBE complexes in Arabidopsis thaliana. The coiled-coil domain of WRKY transcription factors binds to OBE proteins and is responsible for target gene selection and transcriptional repression. The PHD finger of OBE proteins binds to both histones and WRKY transcription factors. WRKY-OBE complexes repress the transcription of numerous stress-responsive genes and are required for maintaining normal plant growth. Several WRKY and OBE mutants show reduced plant size and increased drought tolerance, accompanied by increased expression of stress-responsive genes. Moreover, expression levels of most of these WRKY and OBE genes are reduced in response to drought stress, revealing a previously uncharacterized regulatory mechanism of the drought stress response. These results suggest that WRKY-OBE complexes repress transcription of stress-responsive genes, and thereby balance plant growth and stress tolerance.

Conserved and plant-specific histone acetyltransferase complexes cooperate to regulate gene transcription and plant development.

Although a conserved SAGA complex containing the histone acetyltransferase GCN5 is known to mediate histone acetylation and transcriptional activation in eukaryotes, how to maintain different levels of histone acetylation and transcription at the whole-genome level remains to be determined. Here we identify and characterize a plant-specific GCN5-containing complex, which we term PAGA, in Arabidopsis thaliana and Oryza sativa. In Arabidopsis, the PAGA complex consists of two conserved subunits (GCN5 and ADA2A) and four plant-specific subunits (SPC, ING1, SDRL and EAF6). We find that PAGA and SAGA can independently mediate moderate and high levels of histone acetylation, respectively, thereby promoting transcriptional activation. Moreover, PAGA and SAGA can also repress gene transcription via the antagonistic effect between PAGA and SAGA. Unlike SAGA, which regulates multiple biological processes, PAGA is specifically involved in plant height and branch growth by regulating the transcription of hormone biosynthesis and response related genes. These results reveal how PAGA and SAGA cooperate to regulate histone acetylation, transcription and development. Given that the PAGA mutants show semi-dwarf and increased branching phenotypes without reduction in seed yield, the PAGA mutations could potentially be used for crop improvement.

Comprehensive characterization of three classes of Arabidopsis SWI/SNF chromatin remodelling complexes.

Although SWI/SNF chromatin remodelling complexes are known to regulate diverse biological functions in plants, the classification, compositions and functional mechanisms of the complexes remain to be determined. Here we comprehensively characterized SWI/SNF complexes by affinity purification and mass spectrometry in Arabidopsis thaliana, and found three classes of SWI/SNF complexes, which we termed BAS, SAS and MAS (BRM-, SYD- and MINU1/2-associated SWI/SNF complexes). By investigating multiple developmental phenotypes of SWI/SNF mutants, we found that three classes of SWI/SNF complexes have both overlapping and specific functions in regulating development. To investigate how the three classes of SWI/SNF complexes differentially regulate development, we mapped different SWI/SNF components on chromatin at the whole-genome level and determined their effects on chromatin accessibility. While all three classes of SWI/SNF complexes regulate chromatin accessibility at proximal promoter regions, SAS is a major SWI/SNF complex that is responsible for mediating chromatin accessibility at distal promoter regions and intergenic regions. Histone modifications are related to both the association of SWI/SNF complexes with chromatin and the SWI/SNF-dependent chromatin accessibility. Three classes of SWI/SNF-dependent accessibility may enable different sets of transcription factors to access chromatin. These findings lay a foundation for further investigation of the function of three classes of SWI/SNF complexes in plants.

Characterization of an autonomous pathway complex that promotes flowering in Arabidopsis.

Although previous studies have identified several autonomous pathway components that are required for the promotion of flowering, little is known about how these components cooperate. Here, we identified an autonomous pathway complex (AuPC) containing both known components (FLD, LD and SDG26) and previously unknown components (EFL2, EFL4 and APRF1). Loss-of-function mutations of all of these components result in increased FLC expression and delayed flowering. The delayed-flowering phenotype is independent of photoperiod and can be overcome by vernalization, confirming that the complex specifically functions in the autonomous pathway. Chromatin immunoprecipitation combined with sequencing indicated that, in the AuPC mutants, the histone modifications (H3Ac, H3K4me3 and H3K36me3) associated with transcriptional activation are increased, and the histone modification (H3K27me3) associated with transcriptional repression is reduced, suggesting that the AuPC suppresses FLC expression at least partially by regulating these histone modifications. Moreover, we found that the AuPC component SDG26 associates with FLC chromatin via a previously uncharacterized DNA-binding domain and regulates FLC expression and flowering time independently of its histone methyltransferase activity. Together, these results provide a framework for understanding the molecular mechanism by which the autonomous pathway regulates flowering time.

DIVIS: Integrated and Customizable Pipeline for Cancer Genome Sequencing Analysis and Interpretation.

Next-generation sequencing (NGS) has drastically enhanced human cancer research, but diverse sequencing strategies, complicated open-source software, and the identification of massive numbers of mutations have limited the clinical application of NGS. Here, we first presented GPyFlow, a lightweight tool that flexibly customizes, executes, and shares workflows. We then introduced DIVIS, a customizable pipeline based on GPyFlow that integrates read preprocessing, alignment, variant detection, and annotation of whole-genome sequencing, whole-exome sequencing, and gene-panel sequencing. By default, DIVIS screens variants from multiple callers and generates a standard variant-detection format list containing caller evidence for each sample, which is compatible with advanced analyses. Lastly, DIVIS generates a statistical report, including command lines, parameters, quality-control indicators, and mutation summary. DIVIS substantially facilitates complex cancer genome sequencing analyses by means of a single powerful and easy-to-use command. The DIVIS code is freely available at https://github.com/niu-lab/DIVIS, and the docker image can be downloaded from https://hub.docker.com/repository/docker/sunshinerain/divis.

Comprehensive review and evaluation of computational methods for identifying FLT3-internal tandem duplication in acute myeloid leukaemia.

Internal tandem duplication (ITD) of FMS-like tyrosine kinase 3 (FLT3-ITD) constitutes an independent indicator of poor prognosis in acute myeloid leukaemia (AML). AML with FLT3-ITD usually presents with poor treatment outcomes, high recurrence rate and short overall survival. Currently, polymerase chain reaction and capillary electrophoresis are widely adopted for the clinical detection of FLT3-ITD, whereas the length and mutation frequency of ITD are evaluated using fragment analysis. With the development of sequencing technology and the high incidence of FLT3-ITD mutations, a multitude of bioinformatics tools and pipelines have been developed to detect FLT3-ITD using next-generation sequencing data. However, systematic comparison and evaluation of the methods or software have not been performed. In this study, we provided a comprehensive review of the principles, functionality and limitations of the existing methods for detecting FLT3-ITD. We further compared the qualitative and quantitative detection capabilities of six representative tools using simulated and biological data. Our results will provide practical guidance for researchers and clinicians to select the appropriate FLT3-ITD detection tools and highlight the direction of future developments in this field. Availability: A Docker image with several programs pre-installed is available at https://github.com/niu-lab/docker-flt3-itd to facilitate the application of FLT3-ITD detection tools.

MSIsensor-ct: microsatellite instability detection using cfDNA sequencing data.

MOTIVATION: Microsatellite instability (MSI) is a promising biomarker for cancer prognosis and chemosensitivity. Techniques are rapidly evolving for the detection of MSI from tumor-normal paired or tumor-only sequencing data. However, tumor tissues are often insufficient, unavailable, or otherwise difficult to procure. Increasing clinical evidence indicates the enormous potential of plasma circulating cell-free DNA (cfNDA) technology as a noninvasive MSI detection approach. RESULTS: We developed MSIsensor-ct, a bioinformatics tool based on a machine learning protocol, dedicated to detecting MSI status using cfDNA sequencing data with a potential stable MSIscore threshold of 20%. Evaluation of MSIsensor-ct on independent testing datasets with various levels of circulating tumor DNA (ctDNA) and sequencing depth showed 100% accuracy within the limit of detection (LOD) of 0.05% ctDNA content. MSIsensor-ct requires only BAM files as input, rendering it user-friendly and readily integrated into next generation sequencing (NGS) analysis pipelines. AVAILABILITY: MSIsensor-ct is freely available at https://github.com/niu-lab/MSIsensor-ct. SUPPLEMENTARY INFORMATION: Supplementary data are available at Briefings in Bioinformatics online.

Comprehensive fundamental somatic variant calling and quality management strategies for human cancer genomes.

Next-generation sequencing (NGS) technology has revolutionised human cancer research, particularly via detection of genomic variants with its ultra-high-throughput sequencing and increasing affordability. However, the inundation of rich cancer genomics data has resulted in significant challenges in its exploration and translation into biological insights. One of the difficulties in cancer genome sequencing is software selection. Currently, multiple tools are widely used to process NGS data in four stages: raw sequence data pre-processing and quality control (QC), sequence alignment, variant calling and annotation and visualisation. However, the differences between these NGS tools, including their installation, merits, drawbacks and application, have not been fully appreciated. Therefore, a systematic review of the functionality and performance of NGS tools is required to provide cancer researchers with guidance on software and strategy selection. Another challenge is the multidimensional QC of sequencing data because QC can not only report varied sequence data characteristics but also reveal deviations in diverse features and is essential for a meaningful and successful study. However, monitoring of QC metrics in specific steps including alignment and variant calling is neglected in certain pipelines such as the 'Best Practices Workflows' in GATK. In this review, we investigated the most widely used software for the fundamental analysis and QC of cancer genome sequencing data and provided instructions for selecting the most appropriate software and pipelines to ensure precise and efficient conclusions. We further discussed the prospects and new research directions for cancer genomics.

Genetic algorithm for the optimization of features and neural networks in ECG signals classification.

Feature extraction and classification of electrocardiogram (ECG) signals are necessary for the automatic diagnosis of cardiac diseases. In this study, a novel method based on genetic algorithm-back propagation neural network (GA-BPNN) for classifying ECG signals with feature extraction using wavelet packet decomposition (WPD) is proposed. WPD combined with the statistical method is utilized to extract the effective features of ECG signals. The statistical features of the wavelet packet coefficients are calculated as the feature sets. GA is employed to decrease the dimensions of the feature sets and to optimize the weights and biases of the back propagation neural network (BPNN). Thereafter, the optimized BPNN classifier is applied to classify six types of ECG signals. In addition, an experimental platform is constructed for ECG signal acquisition to supply the ECG data for verifying the effectiveness of the proposed method. The GA-BPNN method with the MIT-BIH arrhythmia database achieved a dimension reduction of nearly 50% and produced good classification results with an accuracy of 97.78%. The experimental results based on the established acquisition platform indicated that the GA-BPNN method achieved a high classification accuracy of 99.33% and could be efficiently applied in the automatic identification of cardiac arrhythmias.

Arrhythmia Classification Based on Multi-Domain Feature Extraction for an ECG Recognition System.

Automatic recognition of arrhythmias is particularly important in the diagnosis of heart diseases. This study presents an electrocardiogram (ECG) recognition system based on multi-domain feature extraction to classify ECG beats. An improved wavelet threshold method for ECG signal pre-processing is applied to remove noise interference. A novel multi-domain feature extraction method is proposed; this method employs kernel-independent component analysis in nonlinear feature extraction and uses discrete wavelet transform to extract frequency domain features. The proposed system utilises a support vector machine classifier optimized with a genetic algorithm to recognize different types of heartbeats. An ECG acquisition experimental platform, in which ECG beats are collected as ECG data for classification, is constructed to demonstrate the effectiveness of the system in ECG beat classification. The presented system, when applied to the MIT-BIH arrhythmia database, achieves a high classification accuracy of 98.8%. Experimental results based on the ECG acquisition experimental platform show that the system obtains a satisfactory classification accuracy of 97.3% and is able to classify ECG beats efficiently for the automatic identification of cardiac arrhythmias.

Heterogeneous integration of a III-V VCSEL light source for optical fiber sensing.

We propose a fiber Bragg grating (FBG) sensor interrogation system utilizing a III-V vertical cavity surface emitting laser (VCSEL) as the on-chip light source. Binary blazed grating (BBG) for coupling between III-V VCSEL and silicon-on-insulator (SOI) waveguides is demonstrated for interrogation of the FBG sensor. The footprint size of the BBG is only 5.62 µm×5.3 µm, and each BBG coupler period has two subperiods. The diameter of the VCSEL's emitting window is 5 µm, which is slightly smaller than that of the BBG coupler, to be well-matched with the proposed structure. Results show that the coupling efficiency from vertical cavities of the III-V VCSEL to the in-plane waveguides reached as high as 32.6% when coupling the 1550.65 nm light. The heterogeneous integration of the III-V VCSEL and SOI waveguides by BBG plays a fundamental role in inducing a great breakthrough to the miniaturization of an on-chip light source for optical fiber sensing.