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Abstract Non-small cell lung cancer (NSCLC) adenocarcinoma (LUAD) is a leading cause of death worldwide. Activating mutations in the tyrosine kinase domain of the oncogene epidermal growth factor receptor (EGFR) are responsible for ~10–50% of all LUAD cases. Although tyrosine kinase inhibitors (TKIs) have been effective in prolonging patient survival and quality of life, acquired resistance and disease progression are inevitable, presenting a clear unmet need for alternative or adjuvant therapeutics. Here we show that an anti-EGFR aptamer (EGFRapt) decreases viability and tumor growth of LUAD cell lines harboring the L858R ± T790M mutation in EGFR. Additionally, we elucidate the mechanism by which EGFRapt exerts these effects by monitoring cellular processes associated with kinase-dependent and kinase-independent mechanisms. Overall, these data establish that EGFRapt has direct anti-cancer activity in mutant EGFR positive LUAD via targetable mechanisms that are independent of existing approaches, and they provide a foundation for further development of nucleic acid-based therapies that target EGFR.

Abstract This strategic plan summarizes the major accomplishments achieved in the last quinquennial by the soybean [Glycine max (L.) Merr.] genetics and genomics research community and outlines key priorities for the next 5 years (2024–2028). This work is the result of deliberations among over 50 soybean researchers during a 2‐day workshop in St Louis, MO, USA, at the end of 2022. The plan is divided into seven traditional areas/disciplines: Breeding, Biotic Interactions, Physiology and Abiotic Stress, Functional Genomics, Biotechnology, Genomic Resources and Datasets, and Computational Resources. One additional section was added, Training the Next Generation of Soybean Researchers, when it was identified as a pressing issue during the workshop. This installment of the soybean genomics strategic plan provides a snapshot of recent progress while looking at future goals that will improve resources and enable innovation among the community of basic and applied soybean researchers. We hope that this work will inform our community and increase support for soybean research.

In mice, the fetal brain is dependent upon the placenta for factors that guide its early development. This linkage between the two organs has given rise to the term, the placenta–brain axis. A similar interrelationship between the two organs may exist in humans. We hypothesize that extracellular vesicles (EVs) released from placental trophoblast (TB) cells transport small RNA and other informational biomolecules from the placenta to the brain where their contents have pleiotropic effects. Here, EVs were isolated from the medium in which human trophoblasts (TBs) had been differentiated in vitro from induced pluripotent stem cells (iPSC) and from cultured iPSC themselves, and their small RNA content analyzed by bulk RNA-seq. EVs derived from human TB cells possess unique profiles of miRs, including hsa-miR-0149-3p, hsa-302a-5p, and many long non-coding RNAs (lncRNAs) relative to EVs isolated from parental iPSC. These miRs and their mRNA targets are enriched in neural tissue. Human neural progenitor cells (NPCs), generated from the same iPSC, were exposed to EVs from either TB or iPSC controls. Both sets of EVs were readily internalized. EVs from TB cells upregulate several transcripts in NPCs associated with forebrain formation and neurogenesis; those from control iPSC upregulated a transcriptional phenotype that resembled glial cells more closely than neurons. These results shed light on the possible workings of the placenta–brain axis. Understanding how the contents of small RNA within TB-derived EVs affect NPCs might yield new insights, possible biomarkers, and potential treatment strategies for neurobehavioral disorders that originate in utero, such as autism spectrum disorders (ASDs).

Chronic kidney disease (CKD) is a leading cause of morbidity and mortality globally. Maternal obesity during pregnancy is linked to systemic inflammation and elevated levels of the pro-inflammatory cytokine interleukin-6 (IL-6). In our previous work, we demonstrated that increased maternal IL-6 during gestation impacts intrauterine development in mice. We hypothesized that IL-6-induced inflammation alters gene expression in the developing fetus. To test this, pregnant mice were administered IL-6 or saline during mid-gestation. Newborn mouse kidneys were analyzed using mRNA-seq, miRNA-seq and whole-genome bisulfite-seq (WGBS). A multi-omics approach was employed to quantify mRNA gene expression, miRNA expression and DNA methylation, using advanced bioinformatics and data integration techniques. Our analysis identified 19 key genes present in multiple omics datasets, regulated by epigenetics and miRNAs. We constructed a regulatory network for these genes, revealing disruptions in pathways such as Mannose type O-glycan biosynthesis, the cell cycle, apoptosis and FoxO signaling. Notably, the Atp7b gene was regulated by DNA methylation and miR-223 targeting, whereas the Man2a1 gene was controlled by DNA methylation affecting energy metabolism. These findings suggest that these genes may play a role in fetal programming, potentially leading to CKD later in life due to gestational inflammation.

Genome-to-phenome research in agriculture aims to improve crops through in silico predictions. Genome-wide association study (GWAS) is potent in identifying genomic loci that underlie important traits. As a statistical method, increasing the sample quantity, data quality, or diversity of the GWAS dataset positively impacts GWAS power. For more precise breeding, concrete candidate genes with exact functional variants must be discovered. Many post-GWAS methods have been developed to narrow down the associated genomic regions and, ideally, to predict candidate genes and causative mutations (CMs). Historical natural selection and breeding-related artificial selection both act to change the frequencies of different alleles of genes that control phenotypes. With higher diversity and more extensive GWAS datasets, there is an increased chance of multiple alleles with independent CMs in a single causal gene. This can be caused by the presence of samples from geographically isolated regions that arose during natural or artificial selection. This simple fact is a complicating factor in GWAS-driven discoveries. Currently, none of the existing association methods address this issue and need to identify multiple alleles and, more specifically, the actual CMs. Therefore, we developed a tool that computes a score for a combination of variant positions in a single candidate gene and, based on the highest score, identifies the best number and combination of CMs. The tool is publicly available as a Python package on GitHub, and we further created a web-based Multiple Alleles discovery (MADis) tool that supports soybean and is hosted in SoyKB (https://soykb.org/SoybeanMADisTool/). We tested and validated the algorithm and presented the utilization of MADis in a pod pigmentation L1 gene case study with multiple CMs from natural or artificial selection. Finally, we identified a candidate gene for the pod color L2 locus and predicted the existence of multiple alleles that potentially cause loss of pod pigmentation. In this work, we show how a genomic analysis can be employed to explore the natural and artificial selection of multiple alleles and, thus, improve and accelerate crop breeding in agriculture.

Abstract Background The advancement of sequencing technologies today has made a plethora of whole-genome re-sequenced (WGRS) data publicly available. However, research utilizing the WGRS data without further configuration is nearly impossible. To solve this problem, our research group has developed an interactive Allele Catalog Tool to enable researchers to explore the coding region allelic variation present in over 1,000 re-sequenced accessions each for soybean, Arabidopsis, and maize. Results The Allele Catalog Tool was designed originally with soybean genomic data and resources. The Allele Catalog datasets were generated using our variant calling pipeline (SnakyVC) and the Allele Catalog pipeline (AlleleCatalog). The variant calling pipeline is developed to parallelly process raw sequencing reads to generate the Variant Call Format (VCF) files, and the Allele Catalog pipeline takes VCF files to perform imputations, functional effect predictions, and assemble alleles for each gene to generate curated Allele Catalog datasets. Both pipelines were utilized to generate the data panels (VCF files and Allele Catalog files) in which the accessions of the WGRS datasets were collected from various sources, currently representing over 1,000 diverse accessions for soybean, Arabidopsis, and maize individually. The main features of the Allele Catalog Tool include data query, visualization of results, categorical filtering, and download functions. Queries are performed from user input, and results are a tabular format of summary results by categorical description and genotype results of the alleles for each gene. The categorical information is specific to each species; additionally, available detailed meta-information is provided in modal popups. The genotypic information contains the variant positions, reference or alternate genotypes, the functional effect classes, and the amino-acid changes of each accession. Besides that, the results can also be downloaded for other research purposes. Conclusions The Allele Catalog Tool is a web-based tool that currently supports three species: soybean, Arabidopsis, and maize. The Soybean Allele Catalog Tool is hosted on the SoyKB website ( https://soykb.org/SoybeanAlleleCatalogTool/ ), while the Allele Catalog Tool for Arabidopsis and maize is hosted on the KBCommons website ( https://kbcommons.org/system/tools/AlleleCatalogTool/Zmays and https://kbcommons.org/system/tools/AlleleCatalogTool/Athaliana ). Researchers can use this tool to connect variant alleles of genes with meta-information of species.

Abstract Certain cultivars of maize show increased tolerance to water deficit conditions by maintenance of root growth. To better understand the molecular mechanisms related to this adaptation, nodal root growth zone samples were collected from the reference inbred line B73 and inbred line FR697, which exhibits a relatively greater ability to maintain root elongation under water deficits. Plants were grown under various water stress levels in both field and controlled environment settings. FR697-specific RNA-Seq datasets were generated and used for a de novo transcriptome assembly to characterize any genotype-specific genetic features. The assembly was aided by an Iso-Seq library of transcripts generated from various FR697 plant tissue samples. The Necklace pipeline was used to combine a Trinity de novo assembly along with a reference guided assembly and the Viridiplantae proteome to generate an annotated consensus “SuperTranscriptome” assembly of 47,915 transcripts with a N50 of 3152 bp in length. The results were compared by Blastn to maize reference genes, a Benchmarking Universal Single-Copy Orthologs (BUSCO) genome completeness report and compared with three maize reference genomes. The resultant ‘SuperTranscriptome’ was demonstrated to be of high-quality and will serve as an important reference for analysis of the maize nodal root transcriptomic response to environmental perturbations.

Sprouty4 (SPRY4) has been frequently reported as a tumor suppressor and is therefore downregulated in various cancers. For the first time, we report that SPRY4 is epigenetically upregulated in colorectal cancer (CRC). In this study, we explored DNA methylation and hydroxymethylation levels of SPRY4 in CRC cells and patient samples and correlated these findings with mRNA and protein expression levels. Three loci within the promoter region of SPRY4 were evaluated for 5mC levels in CRC using the combined bisulfite restriction analysis. In addition, hydroxymethylation levels within SPRY4 were measured in CRC patients. Lastly, DNA methylation and mRNA expression data were extracted from CRC patients in multiple high-throughput data repositories like Gene Expression Omnibus and The Cancer Genome Atlas. Combined in vitro and in silico analysis of promoter methylation levels of SPRY4 clearly demonstrates that the distal promoter region undergoes hypomethylation in CRC patients and is associated with increased expression. Moreover, a decrease in gene body hydroxymethylation and an increase in gene body methylation within the coding region of SPRY4 were found in CRC patients and correlated with increased expression. SPRY4 is epigenetically upregulated in CRC by promoter hypomethylation and hypermethylation within the gene body that warrants future investigation of atypical roles of this established tumor suppressor.

The rapid growth of sequencing technology and its increasing popularity in biology-related research over the years has made whole genome re-sequencing (WGRS) data become widely available. A large amount of WGRS data can unlock the knowledge gap between genomics and phenomics through gaining an understanding of the genomic variations that can lead to phenotype changes. These genomic variations are usually comprised of allele and structural changes in DNA, and these changes can affect the regulatory mechanisms causing changes in gene expression and altering the phenotypes of organisms. In this research work, we created the GenVarX toolset, that is backed by transcription factor binding sequence data in promoter regions, the copy number variations data, SNPs and Indels data, and phenotypes data which can potentially provide insights about phenotypic differences and solve compelling questions in plant research. Analytics-wise, we have developed strategies to better utilize the WGRS data and mine the data using efficient data processing scripts, libraries, tools, and frameworks to create the interactive and visualization-enhanced GenVarX toolset that encompasses both promoter regions and copy number variation analysis components. The main capabilities of the GenVarX toolset are to provide easy-to-use interfaces for users to perform queries, visualize data, and interact with the data. Based on different input windows on the user interface, users can provide inputs corresponding to each field and submit the information as a query. The data returned on the results page is usually displayed in a tabular fashion. In addition, interactive figures are also included in the toolset to facilitate the visualization of statistical results or tool outputs. Currently, the GenVarX toolset supports soybean, rice, and Arabidopsis. The researchers can access the soybean GenVarX toolset from SoyKB via https://soykb.org/SoybeanGenVarX/, rice GenVarX toolset, and Arabidopsis GenVarX toolset from KBCommons web portal with links https://kbcommons.org/system/tools/GenVarX/Osativa and https://kbcommons.org/system/tools/GenVarX/Athaliana, respectively.

Introduction: Inflammatory bowel disease involves aberrant immune responses and is associated with both cardiovascular disease risk and altered intestinal blood flow. However, little is known about how inflammatory bowel disease affects regulation of perivascular nerves that mediate blood flow. Previous work found perivascular nerve function is impaired in mesenteric arteries with Inflammatory bowel disease. The purpose of this study was to determine the mechanism of impaired perivascular nerve function.Methods: RNA sequencing was performed on mesenteric arteries from IL10−/− mice treated with H. hepaticus to induce disease (inflammatory bowel disease) or left non-gavaged (Control). For all other studies, Control and Inflammatory bowel disease mice received either saline or clodronate liposome injections to study the effect of macrophage depletion. Perivascular nerve function was assessed using pressure myography and electrical field stimulation. Leukocyte populations, and perivascular nerves, and adventitial neurotransmitter receptors were labeled using fluorescent immunolabeling.Results: Inflammatory bowel disease was associated with increases in macrophage-associated gene expression, and immunolabeling showed accumulation of adventitial macrophages. Clodronate liposome injection eliminated adventitial macrophages, which reversed significant attenuation of sensory vasodilation, sympathetic vasoconstriction and sensory inhibition of sympathetic constriction in inflammatory bowel disease. Acetylcholine-mediated dilation was impaired in inflammatory bowel disease and restored after macrophage depletion, but sensory dilation remained nitric oxide independent regardless of disease and/or macrophage presence.Conclusion: Altered neuro-immune signaling between macrophages and perivascular nerves in the arterial adventitia contributes to impaired vasodilation, particularly via dilatory sensory nerves. Targeting the adventitial macrophage population may help preserve intestinal blood flow in Inflammatory bowel disease patients.

Abstract Systemic inflammation in pregnant obese women is associated with 1.5- to 2-fold increase in serum Interleukin-6 (IL-6) and newborns with lower kidney/body weight ratio but the role of IL-6 in increased susceptibility to chronic kidney (CKD) in adult progeny is not known. Since IL-6 crosses the placental barrier, we administered recombinant IL-6 (10 pg/g) to pregnant mice starting at mid-gestation yielded newborns with lower body (p

ABSTRACT Opioid drugs are commonly prescribed analgesic to pregnant women. Direct exposure to such drugs may slow gut motility, alter gut permeability, and affect the gut microbiome. While such drugs affect gut microbiome in infants, no study to date has determined whether developmental exposure to such drugs results in longstanding effects on gut microbiota and correspondingly on host responses. We hypothesized developmental exposure to oxycodone (OXY) leads to enduring effects on gut microbiota and such changes are associated with adult neurobehavioral and metabolic changes. Female mice were treated daily with 5 mg OXY/kg or saline solution (control [CTL]) for 2 weeks prior to breeding and then throughout gestation. Male and female offspring pups were weaned, tested with a battery of behavioral and metabolic tests, and fecal boli were collected adulthood (120 days of age). In females, relative abundance of Butyricimonas spp., Bacteroidetes, Anaeroplasma spp., TM7, Enterococcus spp., and Clostridia were greater in OXY versus CTL individuals. In males, relative abundance of Coriobacteriaceae, Roseburia spp., Sutterella spp., and Clostridia were elevated in OXY exposed individuals. Bacterial changes were also associated with predictive metabolite pathway alterations that also varied according to sex. In males and females, affected gut microbiota correlated with metabolic but not behavioral alterations. The findings suggest that developmental exposure to OXY leads to lasting effects on adult gut microbiota that might affect host metabolism, possibly through specific bacterial metabolites or other bacterial-derived products. Further work is needed to characterize how developmental exposure to OXY affects host responses through the gut microbiome. IMPORTANCE This is the first work to show in a rodent model that in utero exposure to an opioid drug can lead to longstanding effects on the gut microbiota when examined at adulthood. Further, such bacterial changes are associated with metabolic host responses. Given the similarities between rodent and human microbiomes, it raises cause for concern that similar effects may become evident in children born to mothers taking oxycodone and other opioid drugs.

Modern soybean [Glycine max (L.) Merr] cultivars have low overall genetic variation due to repeated bottleneck events that arose during domestication and from selection strategies typical of many soybean breeding programs. In both public and private soybean breeding programs, the introgression of wild soybean (Glycine soja Siebold and Zucc.) alleles is a viable option to increase genetic diversity and identify new sources for traits of value. The objectives of our study were to examine the genetic architecture responsible for seed protein and oil using a recombinant inbred line (RIL) population derived from hybridizing a G. max line (‘Osage’) with a G. soja accession (PI 593983). Linkage mapping identified a total of seven significant quantitative trait loci on chromosomes 14 and 20 for seed protein and on chromosome 8 for seed oil with LOD scores ranging from 5.3 to 31.7 for seed protein content and from 9.8 to 25.9 for seed oil content. We analyzed 3,015 single F4:9 soybean plants to develop two residual heterozygotes derived near isogenic lines (RHD-NIL) populations by targeting nine SNP markers from genotype-by-sequencing, which corresponded to two novel quantitative trait loci (QTL) derived from G. soja: one for a novel seed oil QTL on chromosome 8 and another for a novel protein QTL on chromosome 14. Single marker analysis and linkage analysis using 50 RHD-NILs validated the chromosome 14 protein QTL, and whole genome sequencing of RHD-NILs allowed us to reduce the QTL interval from ∼16.5 to ∼4.6 Mbp. We identified two genomic regions based on recombination events which had significant increases of 0.65 and 0.72% in seed protein content without a significant decrease in seed oil content. A new Kompetitive allele-specific polymerase chain reaction (KASP) assay, which will be useful for introgression of this trait into modern elite G. max cultivars, was developed in one region. Within the significantly associated genomic regions, a total of eight genes are considered as candidate genes, based on the presence of gene annotations associated with the protein or amino acid metabolism/movement. Our results provide better insights into utilizing wild soybean as a source of genetic diversity for soybean cultivar improvement utilizing native traits.

Abstract Due to their antimicrobial properties, silver nanoparticles (AgNPs) are used in a wide range of consumer products that includes topical wound dressings, coatings for biomedical devices, and food-packaging to extend the shelf-life. Despite their beneficial antimicrobial effects, developmental exposure to such AgNPs may lead to gut dysbiosis and long-term health consequences in exposed offspring. AgNPs can cross the placenta and blood–brain-barrier to translocate in the brain of offspring. The underlying hypothesis tested in the current study was that developmental exposure of male and female mice to AgNPs disrupts the microbiome–gut–brain axis. To examine for such effects, C57BL6 female mice were exposed orally to AgNPs at a dose of 3 mg/kg BW or vehicle control 2 weeks prior to breeding and throughout gestation. Male and female offspring were tested in various mazes that measure different behavioral domains, and the gut microbial profiles were surveyed from 30 through 120 days of age. Our study results suggest that developmental exposure results in increased likelihood of engaging in repetitive behaviors and reductions in resident microglial cells. Echo-MRI results indicate increased body fat in offspring exposed to AgNPs exhibit. Coprobacillus spp., Mucispirillum spp., and Bifidobacterium spp. were reduced, while Prevotella spp., Bacillus spp., Planococcaceae, Staphylococcus spp., Enterococcus spp., and Ruminococcus spp. were increased in those developmentally exposed to NPs. These bacterial changes were linked to behavioral and metabolic alterations. In conclusion, developmental exposure of AgNPs results in long term gut dysbiosis, body fat increase and neurobehavioral alterations in offspring.

Measurement(s) genetic variation • SNP • Linkage Disequilibrium Technology Type(s) DNA sequencing • bioinformatics analysis • computational phylogenetic analysis Sample Characteristic - Organism Glycine soja • Glycine max Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.13568552

Adaptation of soybean cultivars to the photoperiod in which they are grown is critical for optimizing plant yield. However, despite its importance, only the major loci conferring variation in flowering time and maturity of US soybean have been isolated. By contrast, over 200 genes contributing to floral induction in the model organism Arabidopsis thaliana have been described. In this work, putative alleles of a library of soybean orthologs of these Arabidopsis flowering genes were tested for their latitudinal distribution among elite US soybean lines developed in the United States. Furthermore, variants comprising the alleles of genes with significant differences in latitudinal distribution were assessed for amino acid conservation across disparate genera to infer their impact on gene function. From these efforts, several candidate genes from various biological pathways were identified that are likely being exploited toward adaptation of US soybean to various maturity groups.

Plant tissues are distinguished by their gene expression patterns, which can help identify tissue-specific highly expressed genes and their differential functional modules. For this purpose, large-scale soybean transcriptome samples were collected and processed starting from raw sequencing reads in a uniform analysis pipeline. To address the gene expression heterogeneity in different tissues, we utilized an adversarial deconfounding autoencoder (AD-AE) model to map gene expressions into a latent space and adapted a standard unsupervised autoencoder (AE) model to help effectively extract meaningful biological signals from the noisy data. As a result, four groups of 1,743, 914, 2,107, and 1,451 genes were found highly expressed specifically in leaf, root, seed and nodule tissues, respectively. To obtain key transcription factors (TFs), hub genes and their functional modules in each tissue, we constructed tissue-specific gene regulatory networks (GRNs), and differential correlation networks by using corrected and compressed gene expression data. We validated our results from the literature and gene enrichment analysis, which confirmed many identified tissue-specific genes. Our study represents the largest gene expression analysis in soybean tissues to date. It provides valuable targets for tissue-specific research and helps uncover broader biological patterns. Code is publicly available with open source at https://github.com/LingtaoSu/SoyMeta.

Pancreatic cancer (PaC) is resistant to immune checkpoint therapy, but the underlying mechanisms are largely unknown. In this study, we have established four orthotopic PaC murine models with different PaC cell lines by intra-pancreatic inoculation. Therapeutic examinations demonstrate that only tumors induced with Panc02-H7 cells respond to αPD-1 antibody treatment, leading to significantly reduced tumor growth and increased survival in the recipient mice. Transcriptomic profiling at a single-cell resolution characterizes the molecular activity of different cells within tumors. Comparative analysis and validated experiments demonstrate that αPD-1-sensitive and -resistant tumors differently shape the immune landscape in the tumor microenvironment (TME) and markedly altering effector CD8+ T cells and tumor-associated macrophages (TAMs) in their number, frequency, and gene profile. More exhausted effector CD8+ T cells and increased M2-like TAMs with a reduced capacity of antigen presentation are detected in resistant Panc02-formed tumors versus responsive Panc02-H7-formed tumors. Together, our data highlight the correlation of tumor-induced imbalance of macrophages with the fate of tumor-resident effector CD8+ T cells and PaC response to αPD-1 immunotherapy. TAMs as a critical regulator of tumor immunity and immunotherapy contribute to PaC resistance to immune checkpoint blockade.

Plant growth-promoting bacteria (PGPB) can enhance plant health by facilitating nutrient uptake, nitrogen fixation, protection from pathogens, stress tolerance and/or boosting plant productivity. The genetic determinants that drive the plant–bacteria association remain understudied. To identify genetic loci highly correlated with traits responsive to PGPB, we performed a genome-wide association study (GWAS) using an Arabidopsis thaliana population treated with Azoarcus olearius DQS-4T. Phenotypically, the 305 Arabidopsis accessions tested responded differently to bacterial treatment by improving, inhibiting, or not affecting root system or shoot traits. GWA mapping analysis identified several predicted loci associated with primary root length or root fresh weight. Two statistical analyses were performed to narrow down potential gene candidates followed by haplotype block analysis, resulting in the identification of 11 loci associated with the responsiveness of Arabidopsis root fresh weight to bacterial inoculation. Our results showed considerable variation in the ability of plants to respond to inoculation by A. olearius DQS-4T while revealing considerable complexity regarding statistically associated loci with the growth traits measured. This investigation is a promising starting point for sustainable breeding strategies for future cropping practices that may employ beneficial microbes and/or modifications of the root microbiome.

Discovering gene regulatory relationships and reconstructing gene regulatory networks (GRN) based on gene expression data is a classical, long-standing computational challenge in bioinformatics. Computationally inferring a possible regulatory relationship between two genes can be formulated as a link prediction problem between two nodes in a graph. Graph neural network (GNN) provides an opportunity to construct GRN by integrating topological neighbor propagation through the whole gene network. We propose an end-to-end gene regulatory graph neural network (GRGNN) approach to reconstruct GRNs from scratch utilizing the gene expression data, in both a supervised and a semi-supervised framework. To get better inductive generalization capability, GRN inference is formulated as a graph classification problem, to distinguish whether a subgraph centered at two nodes contains the link between the two nodes. A linked pair between a transcription factor (TF) and a target gene, and their neighbors are labeled as a positive subgraph, while an unlinked TF and target gene pair and their neighbors are labeled as a negative subgraph. A GNN model is constructed with node features from both explicit gene expression and graph embedding. We demonstrate a noisy starting graph structure built from partial information, such as Pearson’s correlation coefficient and mutual information can help guide the GRN inference through an appropriate ensemble technique. Furthermore, a semi-supervised scheme is implemented to increase the quality of the classifier. When compared with established methods, GRGNN achieved state-of-the-art performance on the DREAM5 GRN inference benchmarks. GRGNN is publicly available at https://github.com/juexinwang/GRGNN.

Abstract Background Knowledge Base Commons (KBCommons) v1.1 is a universal and all-inclusive web-based framework providing generic functionalities for storing, sharing, analyzing, exploring, integrating and visualizing multiple organisms’ genomics and integrative omics data. KBCommons is designed and developed to integrate diverse multi-level omics data and to support biological discoveries for all species via a common platform. Methods KBCommons has four modules including data storage, data processing, data accessing, and web interface for data management and retrieval. It provides a comprehensive framework for new plant-specific, animal-specific, virus-specific, bacteria-specific or human disease-specific knowledge base (KB) creation, for adding new genome versions and additional multi-omics data to existing KBs, and for exploring existing datasets within current KBs. Results KBCommons has an array of tools for data visualization and data analytics such as multiple gene/metabolite search, gene family/Pfam/Panther function annotation search, miRNA/metabolite/trait/SNP search, differential gene expression analysis, and bulk data download capacity. It contains a highly reliable data privilege management system to make users’ data publicly available easily and to share private or pre-publication data with members in their collaborative groups safely and securely. It allows users to conduct data analysis using our in-house developed workflow functionalities that are linked to XSEDE high performance computing resources. Using KBCommons’ intuitive web interface, users can easily retrieve genomic data, multi-omics data and analysis results from workflow according to their requirements and interests. Conclusions KBCommons addresses the needs of many diverse research communities to have a comprehensive multi-level OMICS web resource for data retrieval, sharing, analysis and visualization. KBCommons can be publicly accessed through a dedicated link for all organisms at http://kbcommons.org/.

Abstract Objective Soybean seed development is negatively impacted by elevated temperatures during seed fill, which can decrease seed quality and economic value. Prior germplasm screens identified an exotic landrace able to maintain ~ 95% seed germination under stress conditions that reduce germination dramatically (> 50%) for typical soybean seeds. Seed transcriptomic analysis was performed for two soybean lines (a heat-tolerant landrace and a typical high-yielding adapted line) for dry, mature seed, 6-h imbibed seed and germinated seed. Seeds were produced in two environments: a typical Midwestern field and a heat stressed field located in the Midsouth soybean production region. Results Transcriptomic analysis revealed 23–30K expressed genes in each seed tissue sample, and differentially expressed genes (DEGs) with ≥ twofold gene expression differences (at q-value

The autonomous parvovirus Minute Virus of Mice (MVM) localizes to cellular DNA damage sites to establish and sustain viral replication centers, which can be visualized by focal deposition of the essential MVM non-structural phosphoprotein NS1. How such foci are established remains unknown. Here, we show that NS1 localized to cellular sites of DNA damage independently of its ability to covalently bind the 5' end of the viral genome, or its consensus DNA binding sequence. Many of these sites were identical to those occupied by virus during infection. However, localization of the MVM genome to DNA damage sites occurred only when wild-type NS1, but not its DNA-binding mutant was expressed. Additionally, wild-type NS1, but not its DNA binding mutant, could localize a heterologous DNA molecule containing the NS1 binding sequence to DNA damage sites. These findings suggest that NS1 may function as a bridging molecule, helping the MVM genome localize to cellular DNA damage sites to facilitate ongoing virus replication.

AUXIN RESPONSE FACTORS (ARFs) are a family of plant-specific transcriptional factors involved in auxin signaling. Here, the authors adapt DAP-seq technology to show the binding landscape of 14 maize ARFs and reveal class-specific binding properties and transcriptional coordination by ARFs from different classes.

Hyperfiltration is an important underlying cause of glomerular dysfunction associated with several systemic and intrinsic glomerular conditions leading to chronic kidney disease (CKD). These include obesity, diabetes, hypertension, focal segmental glomerulosclerosis (FSGS), congenital abnormalities and reduced renal mass (low nephron number). Hyperfiltration-associated biomechanical forces directly impact the cell membrane, generating tensile and fluid flow shear stresses in multiple segments of the nephron. Ongoing research suggests these biomechanical forces as the initial mediators of hyperfiltration-induced deterioration of podocyte structure and function leading to their detachment and irreplaceable loss from the glomerular filtration barrier. Membrane lipid-derived polyunsaturated fatty acids (PUFA) and their metabolites are potent transducers of biomechanical stress from the cell surface to intracellular compartments. Omega-6 and ω-3 long-chain PUFA from membrane phospholipids generate many versatile and autacoid oxylipins that modulate pro-inflammatory as well as anti-inflammatory autocrine and paracrine signaling. We advance the idea that lipid signaling molecules, related enzymes, metabolites and receptors are not just mediators of cellular stress but also potential targets for developing novel interventions. With the growing emphasis on lifestyle changes for wellness, dietary fatty acids are potential adjunct-therapeutics to minimize/treat hyperfiltration-induced progressive glomerular damage and CKD.