A CTCF-binding site in the Mdm1-Il22-Ifng locus shapes cytokine expression profiles and plays a critical role in early Th1 cell fate specification.

Cytokine expression during T cell differentiation is a highly regulated process that involves long-range promoter-enhancer and CTCF-CTCF contacts at cytokine loci. Here, we investigated the impact of dynamic chromatin loop formation within the topologically associating domain (TAD) in regulating the expression of interferon gamma (IFN-γ) and interleukin-22 (IL-22); these cytokine loci are closely located in the genome and are associated with complex enhancer landscapes, which are selectively active in type 1 and type 3 lymphocytes. In situ Hi-C analyses revealed inducible TADs that insulated Ifng and Il22 enhancers during Th1 cell differentiation. Targeted deletion of a 17 bp boundary motif of these TADs imbalanced Th1- and Th17-associated immunity, both in vitro and in vivo, upon Toxoplasma gondii infection. In contrast, this boundary element was dispensable for cytokine regulation in natural killer cells. Our findings suggest that precise cytokine regulation relies on lineage- and developmental stage-specific interactions of 3D chromatin architectures and enhancer landscapes.

"Stripe" transcription factors provide accessibility to co-binding partners in mammalian genomes.

Regulatory elements activate promoters by recruiting transcription factors (TFs) to specific motifs. Notably, TF-DNA interactions often depend on cooperativity with colocalized partners, suggesting an underlying cis-regulatory syntax. To explore TF cooperativity in mammals, we analyze ∼500 mouse and human primary cells by combining an atlas of TF motifs, footprints, ChIP-seq, transcriptomes, and accessibility. We uncover two TF groups that colocalize with most expressed factors, forming stripes in hierarchical clustering maps. The first group includes lineage-determining factors that occupy DNA elements broadly, consistent with their key role in tissue-specific transcription. The second one, dubbed universal stripe factors (USFs), comprises ∼30 SP, KLF, EGR, and ZBTB family members that recognize overlapping GC-rich sequences in all tissues analyzed. Knockouts and single-molecule tracking reveal that USFs impart accessibility to colocalized partners and increase their residence time. Mammalian cells have thus evolved a TF superfamily with overlapping DNA binding that facilitate chromatin accessibility.

TFSyntax: a database of transcription factors binding syntax in mammalian genomes.

In mammals, transcriptional factors (TFs) drive gene expression by binding to regulatory elements in a cooperative manner. Deciphering the rules of such cooperation is crucial to obtain a full understanding of cellular homeostasis and development. Although this is a long-standing topic, there is no comprehensive database for biologists to access the syntax of TF binding sites. Here we present TFSyntax (https://tfsyntax.zhaopage.com), a database focusing on the arrangement of TF binding sites. TFSyntax maps the binding motif of 1299 human TFs and 890 mouse TFs across 382 cells and tissues, representing the most comprehensive TF binding map to date. In addition to location, TFSyntax defines motif positional preference, density and colocalization within accessible elements. Powered by a series of functional modules based on web interface, users can freely search, browse, analyze, and download data of interest. With comprehensive characterization of TF binding syntax across distinct tissues and cell types, TFSyntax represents a valuable resource and platform for studying the mechanism of transcriptional regulation and exploring how regulatory DNA variants cause disease.

Upraising wavelength exactitude in laser array with spatial hole burning suppression based on the reconstruction-equivalent-chirp technique.

An equivalent corrugation pitch modulated distributed-feedback semiconductor multiwavelength laser array (MLA) with two equivalently assisted phase shifts (EAPSs) based on the reconstruction-equivalent-chirp technique is theoretically studied and experimentally demonstrated. The simulated results show that the longitudinal photon density distribution of the studied MLA is much more uniform than that of the MLA without EAPSs. Accordingly, the longitudinal spatial hole burning of the proposed MLA is therefore suppressed more effectively. The experimental results show that the studied MLA has good single-longitudinal-mode performance. The highest side mode suppression ratio (SMSR) is even up to 52.63 dB. Meanwhile, the tunable wavelength range of the investigated MLA is 25.94 nm under the thermal tuning scheme from 15.12°C to 46.93°C. All channels are within a wavelength deviation of  ±0.001n m. The SMSRs are all above 38 dB.

PADS Arsenal: a database of prokaryotic defense systems related genes.

Defense systems are vital weapons for prokaryotes to resist heterologous DNA and survive from the constant invasion of viruses, and they are widely used in biochemistry investigation and antimicrobial drug research. So far, numerous types of defense systems have been discovered, but there is no comprehensive defense systems database to organize prokaryotic defense gene datasets. To fill this gap, we unveil the prokaryotic antiviral defense system (PADS) Arsenal (https://bigd.big.ac.cn/padsarsenal), a public database dedicated to gathering, storing, analyzing and visualizing prokaryotic defense gene datasets. The initial version of PADS Arsenal integrates 18 distinctive categories of defense system with the annotation of 6 600 264 genes retrieved from 63,701 genomes across 33 390 species of archaea and bacteria. PADS Arsenal provides various ways to retrieve defense systems related genes information and visualize them with multifarious function modes. Moreover, an online analysis pipeline is integrated into PADS Arsenal to facilitate annotation and evolutionary analysis of defense genes. PADS Arsenal can also visualize the dynamic variation information of defense genes from pan-genome analysis. Overall, PADS Arsenal is a state-of-the-art open comprehensive resource to accelerate the research of prokaryotic defense systems.

High-precision channel spacing and balanced output multiwavelength laser array with fine tunability.

The multiwavelength laser array (MLA) with fine wavelength tunability is demonstrated experimentally. The studied MLA has good single-longitudinal-mode performance, and the side-mode suppression ratio (SMSR) even reaches 62.1 dB. Meanwhile, the wavelength range of the MLA can be tuned to 25.003 nm with 63 channels of 50 GHz spacing. All lasers are within a wavelength deviation of ±0.02nm. The output power is almost constant with standard deviation 0.63 dBm. The SMSRs are all above 50 dB.

NucMap: a database of genome-wide nucleosome positioning map across species.

Dynamics of nucleosome positioning affects chromatin state, transcription and all other biological processes occurring on genomic DNA. While MNase-Seq has been used to depict nucleosome positioning map in eukaryote in the past years, nucleosome positioning data is increasing dramatically. To facilitate the usage of published data across studies, we developed a database named nucleosome positioning map (NucMap, http://bigd.big.ac.cn/nucmap). NucMap includes 798 experimental data from 477 samples across 15 species. With a series of functional modules, users can search profile of nucleosome positioning at the promoter region of each gene across all samples and make enrichment analysis on nucleosome positioning data in all genomic regions. Nucleosome browser was built to visualize the profiles of nucleosome positioning. Users can also visualize multiple sources of omics data with the nucleosome browser and make side-by-side comparisons. All processed data in the database are freely available. NucMap is the first comprehensive nucleosome positioning platform and it will serve as an important resource to facilitate the understanding of chromatin regulation.

Comprehensive polychromatic integral diffraction efficiency sensitivity to tilt error for multilayer diffractive optical elements with oblique incidence.

Oblique incidence is the general working state for multilayer diffractive optical elements (MLDOEs) in an imaging optical system. The polychromatic integral diffraction efficiency (PIDE) is very sensitive to the incident angle. Therefore, it is necessary to analyze the effect of tilt error on diffraction efficiency/PIDE with oblique incidence. The theoretical model of the relationship between the diffraction efficiency and tilt error with oblique incidence is presented, and the effect of tilt error on diffraction efficiency/PIDE is analyzed. The analysis model of comprehensive PIDE for a certain range of incident angles and the tilt error for MLDOEs is established. The simulation results showed that the comprehensive PIDE is sensitive to tilt angle with oblique incidence, and the tolerance of the tilt error angle can be determined by the comprehensive PIDE. The tilt error tolerance is furthermore investigated with decenter error based on the maximum of comprehensive PIDE. The method and results can be used to guide the tolerance formulation of tilt error for MLDOEs in hybrid optical systems.

MethBank 3.0: a database of DNA methylomes across a variety of species.

MethBank (http://bigd.big.ac.cn/methbank) is a database that integrates high-quality DNA methylomes across a variety of species and provides an interactive browser for visualization of methylation data. Here, we present an updated implementation of MethBank (version 3.0) by incorporating more DNA methylomes from multiple species and equipping with more enhanced functionalities for data annotation and more friendly web interfaces for data presentation, search and visualization. MethBank 3.0 features large-scale integration of high-quality methylomes, involving 34 consensus reference methylomes derived from a large number of human samples, 336 single-base resolution methylomes from different developmental stages and/or tissues of five plants, and 18 single-base resolution methylomes from gametes and early embryos at multiple stages of two animals. Additionally, it is enhanced by improving the functionalities for data annotation, which accordingly enables systematic identification of methylation sites closely associated with age, sites with constant methylation levels across different ages, differentially methylated promoters, age-specific differentially methylated cytosines/regions, and methylated CpG islands. Moreover, MethBank provides tools to estimate human methylation age online and to identify differentially methylated promoters, respectively. Taken together, MethBank is upgraded with significant improvements and advances over the previous version, which is of great help for deciphering DNA methylation regulatory mechanisms for epigenetic studies.

PGAP-X: extension on pan-genome analysis pipeline.

BACKGROUND: Since PGAP (pan-genome analysis pipeline) was published in 2012, it has been widely employed in bacterial genomics research. Though PGAP has integrated several modules for pan-genomics analysis, how to properly and effectively interpret and visualize the results data is still a challenge. RESULT: To well present bacterial genomic characteristics, a novel cross-platform software was developed, named PGAP-X. Four kinds of data analysis modules were developed and integrated: whole genome sequences alignment, orthologous genes clustering, pan-genome profile analysis, and genetic variants analysis. The results from these analyses can be directly visualized in PGAP-X. The modules for data visualization in PGAP-X include: comparison of genome structure, gene distribution by conservation, pan-genome profile curve and variation on genic and genomic region. Meanwhile, result data produced by other programs with similar function can be imported to be further analyzed and visualized in PGAP-X. To test the performance of PGAP-X, we comprehensively analyzed 14 Streptococcus pneumonia strains and 14 Chlamydia trachomatis. The results show that, S. pneumonia strains have higher diversity on genome structure and gene contents than C. trachomatis strains. In addition, S. pneumonia strains might have suffered many evolutionary events, such genomic rearrangements, frequent horizontal gene transfer, homologous recombination, and other evolutionary process. CONCLUSION: Briefly, PGAP-X directly presents the characteristics of bacterial genomic diversity with different visualization methods, which could help us to intuitively understand dynamics and evolution in bacterial genomes. The source code and the pre-complied executable programs are freely available from http://pgapx.ybzhao.com .

Foxa1 is essential for mammary duct formation.

The transcription factor forkhead box protein A1 (FOXA1) plays a critical role in the proliferation of human breast cancer cells, particularly estrogen receptor alpha (ERα)-positive luminal breast cancer cells. However, genetic studies of the requirement for Foxa1 in mammary tumor formation in mice have been hampered by the lack of a conditional gene ablation. We examined three mouse models of mammary-specific ablation of Foxa1 in ductal epithelial cells to identify the best system for complete and mammary-specific ablation of Foxa1. We found that MMTV-Cre and MMTV-rtTA;Tet-On-Cre led to partial deletion of Foxa1 and attenuated mammary duct formation, whereas Krt14-Cre led to complete ablation of Foxa1 and abolished mammary duct formation, in Foxa1(loxP/loxP) mice. These results demonstrate that Foxa1 is essential for mammary duct formation, and reveal a series of mouse models in which mammary expression of Foxa1 can be attenuated or completely blocked. Our study also suggests a potentially powerful model for complete ablation of Foxa1 in mammary epithelial cells using Krt14-driven Cre expression in an inducible manner, such as Krt14-rtTA;Tet-On-Cre. This model system will facilitate further in vivo functional studies of Foxa1 or other factors in mammary gland development and tumor formation and progression. genesis 54:277-285, 2016. © 2016 Wiley Periodicals, Inc.

Complete genome sequence and comparative genome analysis of a new special Yersinia enterocolitica.

Yersinia enterocolitica is the most diverse species among the Yersinia genera and shows more polymorphism, especially for the non-pathogenic strains. Individual non-pathogenic Y. enterocolitica strains are wrongly identified because of atypical phenotypes. In this study, we isolated an unusual Y. enterocolitica strain LC20 from Rattus norvegicus. The strain did not utilize urea and could not be classified as the biotype. API 20E identified Escherichia coli; however, it grew well at 25 °C, but E. coli grew well at 37 °C. We analyzed the genome of LC20 and found the whole chromosome of LC20 was collinear with Y. enterocolitica 8081, and the urease gene did not exist on the genome which is consistent with the result of API 20E. Also, the 16 S and 23 SrRNA gene of LC20 lay on a branch of Y. enterocolitica. Furthermore, the core-based and pan-based phylogenetic trees showed that LC20 was classified into the Y. enterocolitica cluster. Two plasmids (80 and 50 k) from LC20 shared low genetic homology with pYV from the Yersinia genus, one was an ancestral Yersinia plasmid and the other was novel encoding a number of transposases. Some pathogenic and non-pathogenic Y. enterocolitica-specific genes coexisted in LC20. Thus, although it could not be classified into any Y. enterocolitica biotype due to its special biochemical metabolism, we concluded the LC20 was a Y. enterocolitica strain because its genome was similar to other Y. enterocolitica and it might be a strain with many mutations and combinations emerging in the processes of its evolution.

PanGP: a tool for quickly analyzing bacterial pan-genome profile.

Pan-genome analyses have shed light on the dynamics and evolution of bacterial genome from the point of population. The explosive growth of bacterial genome sequence also brought an extremely big challenge to pan-genome profile analysis. We developed a tool, named PanGP, to complete pan-genome profile analysis for large-scale strains efficiently. PanGP has integrated two sampling algorithms, totally random (TR) and distance guide (DG). The DG algorithm drew sample strain combinations on the basis of genome diversity of bacterial population. The performance of these two algorithms have been evaluated on four bacteria populations with strain numbers varying from 30 to 200, and the DG algorithm exhibited overwhelming advantage on accuracy and stability than the TR algorithm.

VCGDB: a dynamic genome database of the Chinese population.

BACKGROUND: The data released by the 1000 Genomes Project contain an increasing number of genome sequences from different nations and populations with a large number of genetic variations. As a result, the focus of human genome studies is changing from single and static to complex and dynamic. The currently available human reference genome (GRCh37) is based on sequencing data from 13 anonymous Caucasian volunteers, which might limit the scope of genomics, transcriptomics, epigenetics, and genome wide association studies. DESCRIPTION: We used the massive amount of sequencing data published by the 1000 Genomes Project Consortium to construct the Virtual Chinese Genome Database (VCGDB), a dynamic genome database of the Chinese population based on the whole genome sequencing data of 194 individuals. VCGDB provides dynamic genomic information, which contains 35 million single nucleotide variations (SNVs), 0.5 million insertions/deletions (indels), and 29 million rare variations, together with genomic annotation information. VCGDB also provides a highly interactive user-friendly virtual Chinese genome browser (VCGBrowser) with functions like seamless zooming and real-time searching. In addition, we have established three population-specific consensus Chinese reference genomes that are compatible with mainstream alignment software. CONCLUSIONS: VCGDB offers a feasible strategy for processing big data to keep pace with the biological data explosion by providing a robust resource for genomics studies; in particular, studies aimed at finding regions of the genome associated with diseases.

NucMap 2.0: An Updated Database of Genome-wide Nucleosome Positioning Maps Across Species.

Nucleosome dynamics plays important roles in many biological processes, such as DNA replication and gene expression. NucMap (https://ngdc.cncb.ac.cn/nucmap) is the first database of genome-wide nucleosome positioning maps across species. Here, we present an updated version, NucMap 2.0, by incorporating more species and MNase-seq samples. In addition, we integrate other related omics data for each MNase-seq sample to provide a comprehensive view of nucleosome positioning, such as gene expression, transcription factor binding sites, histone modifications and DNA methylation. In particular, NucMap 2.0 integrates and pre-analyzes RNA-seq data and ChIP-seq data of human-related samples, which facilitates the interpretation of nucleosome positioning in humans. All processed data are integrated into an in-built genome browser, and users can make comprehensive side-by-side analyses. In addition, more online analytical functions are developed, which allows researchers to identify differential nucleosome regions and explore potential gene regulatory regions. All resources are open access with a user-friendly web interface.

PGAP: pan-genomes analysis pipeline.

SUMMARY: With the rapid development of DNA sequencing technology, increasing bacteria genome data enable the biologists to dig the evolutionary and genetic information of prokaryotic species from pan-genome sight. Therefore, the high-efficiency pipelines for pan-genome analysis are mostly needed. We have developed a new pan-genome analysis pipeline (PGAP), which can perform five analytic functions with only one command, including cluster analysis of functional genes, pan-genome profile analysis, genetic variation analysis of functional genes, species evolution analysis and function enrichment analysis of gene clusters. PGAP's performance has been evaluated on 11 Streptococcus pyogenes strains. AVAILABILITY: PGAP is developed with Perl script on the Linux Platform and the package is freely available from http://pgap.sf.net. CONTACT: junyu@big.ac.cn; xiaojingfa@big.ac.cn SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Assessment and Optimization of Explainable Machine Learning Models Applied to Transcriptomic Data.

Explainable artificial intelligence aims to interpret how machine learning models make decisions, and many model explainers have been developed in the computer vision field. However, understanding of the applicability of these model explainers to biological data is still lacking. In this study, we comprehensively evaluated multiple explainers by interpreting pre-trained models for predicting tissue types from transcriptomic data and by identifying the top contributing genes from each sample with the greatest impacts on model prediction. To improve the reproducibility and interpretability of results generated by model explainers, we proposed a series of optimization strategies for each explainer on two different model architectures of multilayer perceptron (MLP) and convolutional neural network (CNN). We observed three groups of explainer and model architecture combinations with high reproducibility. Group II, which contains three model explainers on aggregated MLP models, identified top contributing genes in different tissues that exhibited tissue-specific manifestation and were potential cancer biomarkers. In summary, our work provides novel insights and guidance for exploring biological mechanisms using explainable machine learning models.

Development and Validation of an Artificial Intelligence Model for Small Bowel Capsule Endoscopy Video Review.

Importance: Reading small bowel capsule endoscopy (SBCE) videos is a tedious task for clinicians, and a new method should be applied to solve the situation. Objectives: To develop and evaluate the performance of a convolutional neural network algorithm for SBCE video review in real-life clinical care. Design, Setting, and Participants: In this multicenter, retrospective diagnostic study, a deep learning neural network (SmartScan) was trained and validated for the SBCE video review. A total of 2927 SBCE examinations from 29 medical centers were used to train SmartScan to detect 17 types of CE structured terminology (CEST) findings from January 1, 2019, to June 30, 2020. SmartScan was later validated with conventional reading (CR) and SmartScan-assisted reading (SSAR) in 2898 SBCE examinations collected from 22 medical centers. Data analysis was performed from January 25 to December 31, 2021. Exposure: An artificial intelligence-based tool for interpreting clinical images of SBCE. Main Outcomes and Measures: The detection rate and efficiency of CEST findings detected by SSAR and CR were compared. Results: A total of 5825 SBCE examinations were retrospectively collected; 2898 examinations (1765 male participants [60.9%]; mean [SD] age, 49.8 [15.5] years) were included in the validation phase. From a total of 6084 CEST-classified SB findings, SSAR detected 5834 findings (95.9%; 95% CI, 95.4%-96.4%), significantly higher than CR, which detected 4630 findings (76.1%; 95% CI, 75.0%-77.2%). SmartScan-assisted reading achieved a higher per-patient detection rate (79.3% [2298 of 2898]) for CEST findings compared with CR (70.7% [2048 of 2298]; 95% CI, 69.0%-72.3%). With SSAR, the mean (SD) number of images (per SBCE video) requiring review was reduced to 779.2 (337.2) compared with 27 910.8 (12 882.9) with CR, for a mean (SD) reduction rate of 96.1% (4.3%). The mean (SD) reading time with SSAR was shortened to 5.4 (1.5) minutes compared with CR (51.4 [11.6] minutes), for a mean (SD) reduction rate of 89.3% (3.1%). Conclusions and Relevance: This study suggests that a convolutional neural network-based algorithm is associated with an increased detection rate of SBCE findings and reduced SBCE video reading time.

Homology modeling and molecular dynamics simulation studies of human type 1 3ß-hydroxysteroid dehydrogenase: Toward the understanding of cofactor specificity.

The human type 1 isoform of 3ß-hydroxysteroid dehydrogenase is a member of short-chain oxidoreductase family that catalyzes the conversion of dehydroepiandrosterone to androstenedione. To compare the molecular events underlying cofactor specificity in the wild-type and D35A/K36R mutant enzymes, molecular dynamics (MD) simulations of fully solvated cofactor-3ß-HSD1 (wild-type and mutant) complex are performed. Molecular modeling methods are applied to construct three-dimensional models of cofactor-3ß-HSD1 complexes based on Uridine diphosphate (UDP)-galactose 4-epimerase crystal structure from Escherichia coli. The binding mode and binding energy analysis between four different complexes indicate that Asp35 and Lys36 are key residues for the cofactor specificity of 3ß-HSD1, which is in agreement with mutagenesis studies results obtained by Thomas et al.8 The MD results also display that the residue Glu41 may be another important residue except Asp35 and Lys36 for the cofactor specificity and that this result needs further mutational experiment for validation.