SoyMD: a platform combining multi-omics data with various tools for soybean research and breeding.

Advanced multi-omics technologies offer much information that can uncover the regulatory mechanisms from genotype to phenotype. In soybean, numerous multi-omics databases have been published. Although they cover multiple omics, there are still limitations when it comes to the types and scales of omics datasets and analysis methods utilized. This study aims to address these limitations by collecting and integrating a comprehensive set of multi-omics datasets. This includes 38 genomes, transcriptomes from 435 tissue samples, 125 phenotypes from 6686 accessions, epigenome data involving histone modification, transcription factor binding, chromosomal accessibility and chromosomal interaction, as well as genetic variation data from 24 501 soybean accessions. Then, common analysis pipelines and statistical methods were applied to mine information from these multi-omics datasets, resulting in the successful establishment of a user-friendly multi-omics database called SoyMD (https://yanglab.hzau.edu.cn/SoyMD/#/). SoyMD provides researchers with efficient query options and analysis tools, allowing them to swiftly access relevant omics information and conduct comprehensive multi-omics data analyses. Another notable feature of SoyMD is its capability to facilitate the analysis of candidate genes, as demonstrated in the case study on seed oil content. This highlights the immense potential of SoyMD in soybean genetic breeding and functional genomics research.

Expression Atlas update: insights from sequencing data at both bulk and single cell level.

Expression Atlas (www.ebi.ac.uk/gxa) and its newest counterpart the Single Cell Expression Atlas (www.ebi.ac.uk/gxa/sc) are EMBL-EBI's knowledgebases for gene and protein expression and localisation in bulk and at single cell level. These resources aim to allow users to investigate their expression in normal tissue (baseline) or in response to perturbations such as disease or changes to genotype (differential) across multiple species. Users are invited to search for genes or metadata terms across species or biological conditions in a standardised consistent interface. Alongside these data, new features in Single Cell Expression Atlas allow users to query metadata through our new cell type wheel search. At the experiment level data can be explored through two types of dimensionality reduction plots, t-distributed Stochastic Neighbor Embedding (tSNE) and Uniform Manifold Approximation and Projection (UMAP), overlaid with either clustering or metadata information to assist users' understanding. Data are also visualised as marker gene heatmaps identifying genes that help confer cluster identity. For some data, additional visualisations are available as interactive cell level anatomograms and cell type gene expression heatmaps.

CottonMD: a multi-omics database for cotton biological study.

Cotton is an important economic crop, and many loci for important traits have been identified, but it remains challenging and time-consuming to identify candidate or causal genes/variants and clarify their roles in phenotype formation and regulation. Here, we first collected and integrated the multi-omics datasets including 25 genomes, transcriptomes in 76 tissue samples, epigenome data of five species and metabolome data of 768 metabolites from four tissues, and genetic variation, trait and transcriptome datasets from 4180 cotton accessions. Then, a cotton multi-omics database (CottonMD, http://yanglab.hzau.edu.cn/CottonMD/) was constructed. In CottonMD, multiple statistical methods were applied to identify the associations between variations and phenotypes, and many easy-to-use analysis tools were provided to help researchers quickly acquire the related omics information and perform multi-omics data analysis. Two case studies demonstrated the power of CottonMD for identifying and analyzing the candidate genes, as well as the great potential of integrating multi-omics data for cotton genetic breeding and functional genomics research.

The ProteomeXchange consortium at 10 years: 2023 update.

Mass spectrometry (MS) is by far the most used experimental approach in high-throughput proteomics. The ProteomeXchange (PX) consortium of proteomics resources (http://www.proteomexchange.org) was originally set up to standardize data submission and dissemination of public MS proteomics data. It is now 10 years since the initial data workflow was implemented. In this manuscript, we describe the main developments in PX since the previous update manuscript in Nucleic Acids Research was published in 2020. The six members of the Consortium are PRIDE, PeptideAtlas (including PASSEL), MassIVE, jPOST, iProX and Panorama Public. We report the current data submission statistics, showcasing that the number of datasets submitted to PX resources has continued to increase every year. As of June 2022, more than 34 233 datasets had been submitted to PX resources, and from those, 20 062 (58.6%) just in the last three years. We also report the development of the Universal Spectrum Identifiers and the improvements in capturing the experimental metadata annotations. In parallel, we highlight that data re-use activities of public datasets continue to increase, enabling connections between PX resources and other popular bioinformatics resources, novel research and also new data resources. Finally, we summarise the current state-of-the-art in data management practices for sensitive human (clinical) proteomics data.

Integrated Proteomics Analysis of Baseline Protein Expression in Pig Tissues.

The availability of an increasingly large amount of public proteomics data sets presents an opportunity for performing combined analyses to generate comprehensive organism-wide protein expression maps across different organisms and biological conditions. Sus scrofa, a domestic pig, is a model organism relevant for food production and for human biomedical research. Here, we reanalyzed 14 public proteomics data sets from the PRIDE database coming from pig tissues to assess baseline (without any biological perturbation) protein abundance in 14 organs, encompassing a total of 20 healthy tissues from 128 samples. The analysis involved the quantification of protein abundance in 599 mass spectrometry runs. We compared protein expression patterns among different pig organs and examined the distribution of proteins across these organs. Then, we studied how protein abundances were compared across different data sets and studied the tissue specificity of the detected proteins. Of particular interest, we conducted a comparative analysis of protein expression between pig and human tissues, revealing a high degree of correlation in protein expression among orthologs, particularly in brain, kidney, heart, and liver samples. We have integrated the protein expression results into the Expression Atlas resource for easy access and visualization of the protein expression data individually or alongside gene expression data.

The PRIDE database resources in 2022: a hub for mass spectrometry-based proteomics evidences.

The PRoteomics IDEntifications (PRIDE) database (https://www.ebi.ac.uk/pride/) is the world's largest data repository of mass spectrometry-based proteomics data. PRIDE is one of the founding members of the global ProteomeXchange (PX) consortium and an ELIXIR core data resource. In this manuscript, we summarize the developments in PRIDE resources and related tools since the previous update manuscript was published in Nucleic Acids Research in 2019. The number of submitted datasets to PRIDE Archive (the archival component of PRIDE) has reached on average around 500 datasets per month during 2021. In addition to continuous improvements in PRIDE Archive data pipelines and infrastructure, the PRIDE Spectra Archive has been developed to provide direct access to the submitted mass spectra using Universal Spectrum Identifiers. As a key point, the file format MAGE-TAB for proteomics has been developed to enable the improvement of sample metadata annotation. Additionally, the resource PRIDE Peptidome provides access to aggregated peptide/protein evidences across PRIDE Archive. Furthermore, we will describe how PRIDE has increased its efforts to reuse and disseminate high-quality proteomics data into other added-value resources such as UniProt, Ensembl and Expression Atlas.

Expression Atlas update: gene and protein expression in multiple species.

The EMBL-EBI Expression Atlas is an added value knowledge base that enables researchers to answer the question of where (tissue, organism part, developmental stage, cell type) and under which conditions (disease, treatment, gender, etc) a gene or protein of interest is expressed. Expression Atlas brings together data from >4500 expression studies from >65 different species, across different conditions and tissues. It makes these data freely available in an easy to visualise form, after expert curation to accurately represent the intended experimental design, re-analysed via standardised pipelines that rely on open-source community developed tools. Each study's metadata are annotated using ontologies. The data are re-analyzed with the aim of reproducing the original conclusions of the underlying experiments. Expression Atlas is currently divided into Bulk Expression Atlas and Single Cell Expression Atlas. Expression Atlas contains data from differential studies (microarray and bulk RNA-Seq) and baseline studies (bulk RNA-Seq and proteomics), whereas Single Cell Expression Atlas is currently dedicated to Single Cell RNA-Sequencing (scRNA-Seq) studies. The resource has been in continuous development since 2009 and it is available at https://www.ebi.ac.uk/gxa.

Integrated View of Baseline Protein Expression in Human Tissues.

The availability of proteomics datasets in the public domain, and in the PRIDE database, in particular, has increased dramatically in recent years. This unprecedented large-scale availability of data provides an opportunity for combined analyses of datasets to get organism-wide protein abundance data in a consistent manner. We have reanalyzed 24 public proteomics datasets from healthy human individuals to assess baseline protein abundance in 31 organs. We defined tissue as a distinct functional or structural region within an organ. Overall, the aggregated dataset contains 67 healthy tissues, corresponding to 3,119 mass spectrometry runs covering 498 samples from 489 individuals. We compared protein abundances between different organs and studied the distribution of proteins across these organs. We also compared the results with data generated in analogous studies. Additionally, we performed gene ontology and pathway-enrichment analyses to identify organ-specific enriched biological processes and pathways. As a key point, we have integrated the protein abundance results into the resource Expression Atlas, where they can be accessed and visualized either individually or together with gene expression data coming from transcriptomics datasets. We believe this is a good mechanism to make proteomics data more accessible for life scientists.

Comparative transcriptome profiling reveals the multiple levels of crosstalk in phytohormone networks in Brassica napus.

Plant hormones are the intrinsic factors that control plant development. The integration of different phytohormone pathways in a complex network of synergistic, antagonistic and additive interactions has been elucidated in model plants. However, the systemic level of transcriptional responses to hormone crosstalk in Brassica napus is largely unknown. Here, we present an in-depth temporal-resolution study of the transcriptomes of the seven hormones in B. napus seedlings. Differentially expressed gene analysis revealed few common target genes that co-regulated (up- and down-regulated) by seven hormones; instead, different hormones appear to regulate distinct members of protein families. We then constructed the regulatory networks between the seven hormones side by side, which allowed us to identify key genes and transcription factors that regulate the hormone crosstalk in B. napus. Using this dataset, we uncovered a novel crosstalk between gibberellin and cytokinin in which cytokinin homeostasis was mediated by RGA-related CKXs expression. Moreover, the modulation of gibberellin metabolism by the identified key transcription factors was confirmed in B. napus. Furthermore, all data were available online from http://yanglab.hzau.edu.cn/BnTIR/hormone. Our study reveals an integrated hormone crosstalk network in Brassica napus, which also provides a versatile resource for future hormone studies in plant species.

Integrated view and comparative analysis of baseline protein expression in mouse and rat tissues.

The increasingly large amount of proteomics data in the public domain enables, among other applications, the combined analyses of datasets to create comparative protein expression maps covering different organisms and different biological conditions. Here we have reanalysed public proteomics datasets from mouse and rat tissues (14 and 9 datasets, respectively), to assess baseline protein abundance. Overall, the aggregated dataset contained 23 individual datasets, including a total of 211 samples coming from 34 different tissues across 14 organs, comprising 9 mouse and 3 rat strains, respectively. In all cases, we studied the distribution of canonical proteins between the different organs. The number of canonical proteins per dataset ranged from 273 (tendon) and 9,715 (liver) in mouse, and from 101 (tendon) and 6,130 (kidney) in rat. Then, we studied how protein abundances compared across different datasets and organs for both species. As a key point we carried out a comparative analysis of protein expression between mouse, rat and human tissues. We observed a high level of correlation of protein expression among orthologs between all three species in brain, kidney, heart and liver samples, whereas the correlation of protein expression was generally slightly lower between organs within the same species. Protein expression results have been integrated into the resource Expression Atlas for widespread dissemination.

Septin 9 methylation analysis of lymph node micrometastases for predicting relapse of colorectal cancer.

BACKGROUND: Molecular markers for the detection of lymph node micrometastases of malignant tumors have been extensively investigated. However, epigenetic signatures have rarely been reported for identification of metastatic lymph nodes and disease relapse. Septin 9 is the most frequently reported hypermethylated gene in colorectal cancer (CRC). This study aimed to assess the clinical relevance of Septin 9 methylation in regional lymph nodes in recurrence/metastases of CRC. METHODS: We analyzed Septin 9 methylation of DNA from resected lymph nodes in 75 CRC patients with or without tumor recurrence using quantitative methylation-sensitive PCR (qMS-PCR). RESULTS: Of the 30 histologically negative lymph node CRC patients without recurrence (group 1), methylated Septin 9 was detected in 3 (10 %) cases. The positivity rate of methylated Septin 9 in group 2 containing 30 histologically node-negative CRC patients with recurrence was 30 % (9/30). For group 3, lymphatic invasion as well as tumor recurrence, 11 (73 %) out of 15 subjects had Septin 9 methylation-positive lymph nodes. Moreover, patients in group 3 had a higher level of methylated Septin 9 compared to subjects in group 1 and group 2 (p < 0.05). In addition, CRC patients with Septin 9 methylation in lymph nodes had significantly reduced survival (Log-rank P < 0.0001). CONCLUSION: Our data support the predictive role of Septin 9 methylation analysis of lymph node micrometastases for tumor relapse after surgery.

Sodium houttuyfonate attenuates neurological defects after traumatic brain injury in mice via inhibiting NLRP3 inflammasomes.

Sodium houttuyfonate (SH) is a chemical compound synthesized by houttuynin and sodium bisulfite. As it has antinflammatory effects, SH has been widely used to treat autoimmune diseases, including post events following traumatic brain injury (TBI). Meanwhile, NOD-like receptor with pyrin domain containing-3 (NLRP3) inflammasomes in microglia may play a central role in TBI. But to date, the intracellular mechanisms involved in the anti-inflammatory effects of SH in TBI remain unknown, especially whether regulating NLRP3. To gain an insight into this possibility, we conducted cell culture and biochemical studies on the effect of SH on NLRP3 inflammasome in microglia. The results showed that SH inhibited TLR4 and NLRP3 inflammasome activation in the microglia cell. In parallel, phosphorylation of ERK and NF-κB p65, which play a key role in NLRP3 inflammasome formation, was decreased. Intraperitoneal injection of SH into TBI mice significantly reduced the modified neurological severity score (mNSS), as well as the degree of microglia apoptosis post-controlled cortical impact (CCI). Immunohistochemistry, Western blot analysis, and reverse-transcription polymerase chain reaction (RT-PCR) revealed that SH markedly reduced NLRP3 inflammasome activation, TLR4 activity, phosphorylation of ERK and NF-κB. Moreover, SH significantly inhibited microglia activation post-CCI, but effectively promoted the astrocyte activation and angiopoiesis. Taken together, our research provides evidence that SH attenuated neurological deficits post TBI through inhibiting NLRP3 inflammasome activation, via influencing the TLR4/NF-κB signaling pathway. These findings explain the intracellular mechanism of the anti-inflammatory activity caused by SH treatment following TBI.

Counterion binding on coacervation of dioctyl sulfosuccinate in aqueous sodium chloride.

A simple coacervate-forming system consisting of sodium dioctyl sulfosuccinate (DOSS) in aqueous NaCl solution was investigated by turbidity measurement, electromotive force measurement (EMF), dynamic light scattering (DLS), and cryogenic transmission electron microscopy (cryo-TEM) to reveal the role of counterion binding in the microstructural changes behind the evolution of the coacervate phase. Coacervation phase boundaries of DOSS against different NaCl concentrations were obtained; the pseudo-coacervation constant, Ksp,co = [DOSS-][Na+], was determined to be 1.35 ± 0.15 × 10-4 M2 at 25 °C. Sodium ion activity from EMF measurements confirmed a drastic rise in counterion binding to DOSS aggregates near the coacervate phase boundary. For DOSS/NaCl solution concentrations near the coacervate phase boundary, the turbidity changed, starting from a clear, isotropic solution far from the phase boundary, transitioning to a turbid solution near the phase boundary, and exhibiting a distinct growth of the hydrodynamic diameter of DOSS aggregates as detected by DLS. Cryo-TEM evidenced the presence of vesicles at concentrations close to the coacervate phase boundary; both unilamellar and multilamellar vesicles were observed. Increased counterion binding on the aggregates led to fusion of the larger vesicles and eventually to formation of a coacervate phase; the DOSS aggregates in the clear supernatant phase were predominately small vesicles of approximately 100 nm diameter. This study suggests that the mechanism for coacervate formation in DOSS solutions is an increase in counterion binding coincident with formation of multilamellar vesicles near the phase boundary, followed by flocculation of the multilamellar vesicles beyond the phase boundary to form the coacervate phase.

Grating-tuned dual-wavelength Nile red dye laser.

Dual-wavelength operation of grating-tuned dye laser systems was demonstrated in this paper. We used the second harmonic generation of a Q-switched Nd:YAG laser to pump the Nile red solvent (dissolved in ethanol) in the Littrow configuration and the Littman-Metcalf configuration. By rotating the grating 3.6° in the Littrow configuration and the tuning mirror 3.9° in the Littman-Metcalf configuration, we obtained a 72 and 46 nm tuning-range dye laser output, respectively. Meanwhile by parallelly moving the grating in the Littrow configuration and the tuning mirror in the Littman-Metcalf configuration, we achieved the separation of dual wavelength from 0.7 to 5 nm in the former and 1.5 to 4 nm in the latter, which were in the terahertz range and could find applications in the terahertz source after using difference frequency technology. Finally, after considering the laser trajectories in the two configurations, we theoretically analyzed the reasons for overall tuning and separation tuning of dual wavelength.

[Multi-Element Detection in Molten Steel with Laser-Induced Breakdown Spectroscopy].

On-line element content detection in iron and steel industry is one of the key techniques to ensure the quality in iron and steel metallurgy. Laser Induced Breakdown Spectroscopy (LIBS) has been applied to on-line components detection in molten steel. We have built LIBS system for components detection of molten steel in laboratory. The system consists of a Q-switched Nd∶YAG laser (repetition rate 10 Hz, wavelength 1 064 nm, pulse length 10 ns, pulse energy about 120 mJ), high frequency induction furnace (temperature 1 600 ℃), spectrometer (wavelength range 186～310 nm, spectral resolution 0.1 nm), laser focusing and spectral signal collecting system. Multi-elements were detected in molten steel with the application of deep-UV detector coating and solarization resistant fibers. According to the calibration curves of C, S, Mn and Cr, the limit of detections are 169, 15, 58.9 and 210 µg·g-1 respectively. The R-squares of calibration curves of C, S, Mn, and Cr are better than 0.96 by using appropriate analytical lines and reference lines. At the same time, through the comparison of different elements, we find the best calibration curve of different element need different delay conditions.

[The auto-focusing remote laser-induced breakdown spectroscopy system].

The present paper presents an auto-focus laser-induced breakdown spectroscopy (LIBS) remote measuring system. This system contains a Schwarzschild telescope, which consists of a convex mirror and a concave mirror. The two spherical mirrors are coaxially placed. The convex mirror is mounted on a motorized linear translation stage. With this motorized linear translation stage, the convex mirror can move along the optical axis to change the spacing between the convex mirror and the concave mirror. Therefore the focal length can be adjusted to focus the laser on samples at different distances and collect the plasma spectra. The advantages of the telescope system include, firstly, the light path of laser focusing and spectra signal collection is the same, which make it easier for mounting and collimation; secondly, the light path of the telescope uses total reflection type, which is fit for the detection in ultra-violate region; finally, the telescope consists of only two spherical mirrors which are relatively easier to manufacture. Within the translation range of the motorized linear translation stage, the focal length of the telescope in this paper can be adjusted from 1.5 to 3.6 m. The diameter of the focusing spot varies from 0.5 to 1.0 mm. Utilizing this telescope system, LIBS experiments were conducted using copper sample. And the characteristic lines of Cu element (Cu I 223.01 nm, Cu I 224.43 nm) obtained are used for the auto focusing. By investigating the relation of the area of spectral lines covered and the spacing between the mirrors, the optimal laser focusing location was obtained. The LIBS experiment results show that the system functions well, fulfilling the demand of remote ablation of sample and LIBS spectral measuring, and the telescope is able to auto-focus the laser on samples at different position to perform remote LIBS experiment.

High k nanophase zinc oxide on biomimetic silicon nanotip array as supercapacitors.

A 3D trenched-structure metal-insulator-metal (MIM) nanocapacitor array with an ultrahigh equivalent planar capacitance (EPC) of ~300 µF cm(-2) is demonstrated. Zinc oxide (ZnO) and aluminum oxide (Al2O3) bilayer dielectric is deposited on 1 µm high biomimetic silicon nanotip (SiNT) substrate using the atomic layer deposition method. The large EPC is achieved by utilizing the large surface area of the densely packed SiNT (!5 × 10(10) cm(-2)) coated conformally with an ultrahigh dielectric constant of ZnO. The EPC value is 30 times higher than those previously reported in metal-insulator-metal or metal-insulator-semiconductor nanocapacitors using similar porosity dimensions of the support materials.

[A method for time-resolved laser-induced breakdown spectroscopy measurement].

Laser-Induced Breakdown Spectroscopy (LIBS) is strongly time related. Time-resolved LIBS measurement is an important technique for the research on laser induced plasma evolution and self-absorption of the emission lines. Concerning the temporal characteristics of LIBS spectrum, a method is proposed in the present paper which can achieve micros-scale time-resolved LIBS measurement by using general ms-scale detector. By setting different integration delay time of the ms-scale spectrum detector, a series of spectrum are recorded. And the integration delay time interval should be longer than the worst temporal precision. After baseline correction and spectrum fitting, the intensity of the character line was obtained. Calculating this intensity with differential method at a certain time interval and then the difference value is the time-resolved line intensity. Setting the plasma duration time as X-axis and the time-resolved line intensity as Y-axis, the evolution curve of the character line intensity can be plotted. Character line with overlap-free and smooth background should be a priority to be chosen for analysis. Using spectrometer with ms-scale integration time and a control system with temporal accuracy is 0.021 micros, experiments carried out. The results validate that this method can be used to characterize the evolution of LIBS characteristic lines and can reduce the cost of the time-resolved LIBS measurement system. This method makes high time-resolved LIBS spectrum measurement possible with cheaper system.

CSANet: a lightweight channel and spatial attention neural network for grading diabetic retinopathy with optical coherence tomography angiography.

Background: Diabetic retinopathy (DR) is one of the most common eye diseases. Convolutional neural networks (CNNs) have proven to be a powerful tool for learning DR features; however, accurate DR grading remains challenging due to the small lesions in optical coherence tomography angiography (OCTA) images and the small number of samples. Methods: In this article, we developed a novel deep-learning framework to achieve the fine-grained classification of DR; that is, the lightweight channel and spatial attention network (CSANet). Our CSANet comprises two modules: the baseline model, and the hybrid attention module (HAM) based on spatial attention and channel attention. The spatial attention module is used to mine small lesions and obtain a set of spatial position weights to address the problem of small lesions being ignored during the convolution process. The channel attention module uses a set of channel weights to focus on useful features and suppress irrelevant features. Results: The extensive experimental results for the OCTA-DR and diabetic retinopathy analysis challenge (DRAC) 2022 data sets showed that the CSANet achieved state-of-the-art DR grading results, showing the effectiveness of the proposed model. The CSANet had an accuracy rate of 97.41% for the OCTA-DR data set and 85.71% for the DRAC 2022 data set. Conclusions: Extensive experiments using the OCTA-DR and DRAC 2022 data sets showed that the proposed model effectively mitigated the problems of mutual confusion between DRs of different severity and small lesions being neglected in the convolution process, and thus improved the accuracy of DR classification.