MOTIVATION: Next-generation sequencing technologies generate millions of short sequence reads, which are usually aligned to a reference genome. In many applications, the key information required for downstream analysis is the number of reads mapping to each genomic feature, for example to each exon or each gene. The process of counting reads is called read summarization. Read summarization is required for a great variety of genomic analyses but has so far received relatively little attention in the literature. RESULTS: We present featureCounts, a read summarization program suitable for counting reads generated from either RNA or genomic DNA sequencing experiments. featureCounts implements highly efficient chromosome hashing and feature blocking techniques. It is considerably faster than existing methods (by an order of magnitude for gene-level summarization) and requires far less computer memory. It works with either single or paired-end reads and provides a wide range of options appropriate for different sequencing applications. AVAILABILITY AND IMPLEMENTATION: featureCounts is available under GNU General Public License as part of the Subread (http://subread.sourceforge.net) or Rsubread (http://www.bioconductor.org) software packages.

featureCounts: an efficient general-purpose program for assigning sequence reads to genomic features

Functional analysis of large gene lists, derived in most cases from emerging high-throughput genomic, proteomic and bioinformatics scanning approaches, is still a challenging and daunting task. The gene-annotation enrichment analysis is a promising high-throughput strategy that increases the likelihood for investigators to identify biological processes most pertinent to their study. Approximately 68 bioinformatics enrichment tools that are currently available in the community are collected in this survey. Tools are uniquely categorized into three major classes, according to their underlying enrichment algorithms. The comprehensive collections, unique tool classifications and associated questions/issues will provide a more comprehensive and up-to-date view regarding the advantages, pitfalls and recent trends in a simpler tool-class level rather than by a tool-by-tool approach. Thus, the survey will help tool designers/developers and experienced end users understand the underlying algorithms and pertinent details of particular tool categories/tools, enabling them to make the best choices for their particular research interests.

/pdf/bioinformatics-enrichment-tools-paths-toward-the-2yo1xl3r2j.pdf

Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists

The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but epigenomic studies lack a similar reference. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection so far of human epigenomes for primary cells and tissues. Here we describe the integrative analysis of 111 reference human epigenomes generated as part of the programme, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression. We establish global maps of regulatory elements, define regulatory modules of coordinated activity, and their likely activators and repressors. We show that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease. Our results demonstrate the central role of epigenomic information for understanding gene regulation, cellular differentiation and human disease.

/pdf/integrative-analysis-of-111-reference-human-epigenomes-4bavnjaon6.pdf

Integrative analysis of 111 reference human epigenomes

We present GOseq, an application for performing Gene Ontology (GO) analysis on RNA-seq data. GO analysis is widely used to reduce complexity and highlight biological processes in genome-wide expression studies, but standard methods give biased results on RNA-seq data due to over-detection of differential expression for long and highly expressed transcripts. Application of GOseq to a prostate cancer data set shows that GOseq dramatically changes the results, highlighting categories more consistent with the known biology.

/pdf/gene-ontology-analysis-for-rna-seq-accounting-for-selection-456k6bns5w.pdf

Gene ontology analysis for RNA-seq: accounting for selection bias

Outcomes of high-throughput biological experiments are typically interpreted by statistical testing for enriched gene functional categories defined by the Gene Ontology (GO). The resulting lists of GO terms may be large and highly redundant, and thus difficult to interpret.

REVIGO is a Web server that summarizes long, unintelligible lists of GO terms by finding a representative subset of the terms using a simple clustering algorithm that relies on semantic similarity measures. Furthermore, REVIGO visualizes this non-redundant GO term set in multiple ways to assist in interpretation: multidimensional scaling and graph-based visualizations accurately render the subdivisions and the semantic relationships in the data, while treemaps and tag clouds are also offered as alternative views. REVIGO is freely available at http://revigo.irb.hr/.

/pdf/revigo-summarizes-and-visualizes-long-lists-of-gene-ontology-3taarmiz8n.pdf

REVIGO Summarizes and Visualizes Long Lists of Gene Ontology Terms

http://www.mcponline.org/article/S1535947622002985/pdf

Lysine Succinylation of VBS Contributes to Sclerotia Development and Aflatoxin Biosynthesis in Aspergillus flavus

Auxin-inducible degron (AID) technology is powerful for chemogenetic control of proteolysis. However, generation of human cell lines to deplete endogenous proteins with AID remains challenging. Typically, homozygous degron-tagging efficiency is low and overexpression of an auxin receptor requires additional engineering steps. Here, we establish a one-step genome editing procedure with high-efficiency homozygous tagging and auxin receptor expression. We demonstrate its application in 5 human cell lines, including embryonic stem (ES) cells. The method allowed isolation of AID single-cell clones in 10 days for 11 target proteins with >80% average homozygous degron-tagging efficiency in A431 cells, and >50% efficiency for 5 targets in H9 ES cells. The tagged endogenous proteins were inducibly degraded in all cell lines, including ES cells and ES-cell derived neurons, with robust expected functional readouts. This method facilitates the application of AID for studying endogenous protein functions in human cells, especially in stem cells.

/pdf/one-step-generation-of-auxin-inducible-degron-cells-with-2hizx2sr.pdf

One-step generation of auxin-inducible degron cells with high-efficiency homozygous tagging

Infrared and visible image fusion (IVIF) aims to provide informative images by combining complementary information from different sensors. Existing IVIF methods based on deep learning focus on strengthening the network with increasing depth but often ignore the importance of transmission characteristics, resulting in the degradation of important information. In addition, while many methods use various loss functions or fusion rules to retain complementary features of both modes, the fusion results often retain redundant or even invalid information.In order to accurately extract the effective information from both infrared images and visible light images without omission or redundancy, and to better serve downstream tasks such as target detection with the fused image, we propose a multi-level structure search attention fusion network based on semantic information guidance, which realizes the fusion of infrared and visible images in an end-to-end way. Our network has two main contributions: the use of neural architecture search (NAS) and the newly designed multilevel adaptive attention module (MAAB). These methods enable our network to retain the typical characteristics of the two modes while removing useless information for the detection task in the fusion results. In addition, our loss function and joint training method can establish a reliable relationship between the fusion network and subsequent detection tasks. Extensive experiments on the new dataset (M3FD) show that our fusion method has achieved advanced performance in both subjective and objective evaluations, and the mAP in the object detection task is improved by 0.5% compared to the second-best method (FusionGAN).

Multi-Modality Image Fusion and Object Detection Based on Semantic Information

The bokeh effect is an artistic technique that blurs out-of-focus areas in a photograph and has gained interest due to recent developments in text-to-image synthesis and the ubiquity of smart-phone cameras and photo-sharing apps. Prior work on rendering bokeh effects have focused on post hoc image manipulation to produce similar blurring effects in existing photographs using classical computer graphics or neural rendering techniques, but have either depth discontinuity artifacts or are restricted to reproducing bokeh effects that are present in the training data. More recent diffusion based models can synthesize images with an artistic style, but either require the generation of high-dimensional masks, expensive fine-tuning, or affect global image characteristics. In this paper, we present GBSD, the first generative text-to-image model that synthesizes photorealistic images with a bokeh style. Motivated by how image synthesis occurs progressively in diffusion models, our approach combines latent diffusion models with a 2-stage conditioning algorithm to render bokeh effects on semantically defined objects. Since we can focus the effect on objects, this semantic bokeh effect is more versatile than classical rendering techniques. We evaluate GBSD both quantitatively and qualitatively and demonstrate its ability to be applied in both text-to-image and image-to-image settings.

GBSD: Generative Bokeh with Stage Diffusion

The roadway of an abandoned mine is an ideal site for the construction of underground pumped storage hydropower, but the operation of the power station is deeply restricted by the structural characteristics of the roadway. With the common double-bend roadway of an abandoned mine as the research object, this study conducted numerical simulations based on the theory of mass conservation and momentum conservation and explored the law of the flow field characteristics and energy loss of a double-bend roadway with the roadway structure and angle. The results showed that a velocity gradient and a pressure gradient form from the outer wall to the inner wall when the fluid flows through the two bends of the roadway. The low-speed zone and maximum positive pressure appeared at the outside of the bend, while the high-speed zone and maximum negative pressure appeared at the inside of the bend. As the angle rose, the peak value of positive pressure increased correspondingly when the fluid flowed through Model A, whereas the negative pressure displayed a fluctuating trend of increasing first and then decreasing and reached its peak when β = 45°. By contrast, when the fluid flowed through Model B, the velocity gradient was symmetrically distributed at the two bends. The peak value of the positive pressure of the first bend increased, and the other positive and negative pressures displayed a trend of “first increasing and then decreasing” when the angle increased, and they reached their peak when β = 45°. When β ≥ 60°, the fluid formed a backflow zone when it flowed through each bend. With an increase in the angle, the area of the backflow zone increased correspondingly. The head loss of the two models increased with the angle. At the same angle, the head loss of Model B was greater than that of Model A. According to the requirement of abandoned mine pumped storage, the roadways with a bend angle of 15° or 30° in Model A and 15° in Model B can be used. The research results can provide some reference for the underground space exploitation and utilization of abandoned mine pumped storage.

/pdf/hydraulic-characteristics-analysis-of-double-bend-roadway-of-1dlwr9wb.pdf

Xin Zhou

Papers

Lysine Succinylation of VBS Contributes to Sclerotia Development and Aflatoxin Biosynthesis in Aspergillus flavus

One-step generation of auxin-inducible degron cells with high-efficiency homozygous tagging

Multi-Modality Image Fusion and Object Detection Based on Semantic Information

GBSD: Generative Bokeh with Stage Diffusion

Hydraulic Characteristics Analysis of Double-Bend Roadway of Abandoned Mine Pumped Storage