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Multiple sclerosis(MS), primary Sjögren syndrome (pSS), and systemic lupus erythematosus (SLE) share numerous clinical symptoms and serological characteristics. We analyzed 153550 cells of scRNA-seq data of 17 treatment-naive patients (5 MS, 5 pSS, and 7 SLE) and 10 healthy controls, and we examined the enrichment of biological processes, differentially expressed genes (DEGs), immune cell types, and their subpopulations, and cell-cell communication in peripheral blood mononuclear cells (PBMCs). The percentage of B cells, megakaryocytes, monocytes, and proliferating T cells presented significant changes in autoimmune diseases. The enrichment of cell types based on gene expression revealed an elevated monocyte. MIF, MK, and GALECTIN signaling networks were obvious differences in autoimmune diseases. Taken together, our analysis provides a comprehensive map of the cell types and states of ADs patients at the single-cell level to understand better the pathogenesis and treatment of these ADs. • 234 common differentially expressed genes overlapped across SLE, MS, pSS, and HC groups. • Monocyte expansion contributes to the pathogenesis of these autoimmune diseases. • B cells, megakaryocytes, monocytes, and proliferating T cells significantly change in autoimmune diseases. • MIF, MK, and GALECTIN signaling pathways play an essential role in SLE, MS, and pSS patients. [ABSTRACT FROM AUTHOR]

Drought and heat stress substantially impact plant growth and productivity. When subjected to drought or heat stress, plants exhibit reduction in growth resulting in yield losses. The occurrence of these two stresses together intensifies their negative effects. Unraveling the molecular changes in response to combined abiotic stress is essential to breed climate-resilient crops. In this study, transcriptome profiles were compared between stress-tolerant (Otis), and stress-sensitive (Golden Promise) barley genotypes subjected to drought, heat, and combined heat and drought stress for five days during heading stage. The major differences that emerged from the transcriptome analysis were the overall number of differentially expressed genes was relatively higher in Golden Promise (GP) compared to Otis. The differential expression of more than 900 transcription factors in GP and Otis may aid this transcriptional reprogramming in response to abiotic stress. Secondly, combined heat and water deficit stress results in a unique and massive transcriptomic response that cannot be predicted from individual stress responses. Enrichment analyses of gene ontology terms revealed unique and stress type-specific adjustments of gene expression. Weighted Gene Co-expression Network Analysis identified genes associated with RNA metabolism and Hsp70 chaperone components as hub genes that can be useful for engineering tolerance to multiple abiotic stresses. Comparison of the transcriptomes of unstressed Otis and GP plants identified several genes associated with biosynthesis of antioxidants and osmolytes were higher in the former that maybe providing innate tolerance capabilities to effectively combat hostile conditions. Lines with different repertoire of innate tolerance mechanisms can be effectively leveraged in breeding programs for developing climate-resilient barley varieties with superior end-use traits. [ABSTRACT FROM AUTHOR]

Previous studies report that the asymmetric response, observed along the main poplar woody bent root axis, was strongly related to both the type of mechanical forces (compression or tension) and the intensity of force displacement. Despite a large number of targets that have been proposed to trigger this asymmetry, an understanding of the comprehensive and synergistic effect of the antistress spatially related pathways is still lacking. Recent progress in the bioinformatics area has the potential to fill these gaps through the use of in silico studies, able to investigate biological functions and pathway overlaps, and to identify promising targets in plant responses. Presently, for the first time, a comprehensive network-based analysis of proteomic signatures was used to identify functions and pivotal genes involved in the coordinated signalling pathways and molecular activities that asymmetrically modulate the response of different bent poplar root sectors and sides. To accomplish this aim, 66 candidate proteins, differentially represented across the poplar bent root sides and sectors, were grouped according to their abundance profile patterns and mapped, together with their first neighbours, on a high-confidence set of interactions from STRING to compose specific cluster-related subnetworks (I–VI). Successively, all subnetworks were explored by a functional gene set enrichment analysis to identify enriched gene ontology terms. Subnetworks were then analysed to identify the genes that are strongly interconnected with other genes (hub gene) and, thus, those that have a pivotal role in the bent root asymmetric response. The analysis revealed novel information regarding the response coordination, communication, and potential signalling pathways asymmetrically activated along the main root axis, delegated mainly to Ca2+ (for new lateral root formation) and ROS (for gravitropic response and lignin accumulation) signatures. Furthermore, some of the data indicate that the concave side of the bent sector, where the mechanical forces are most intense, communicates to the other (neighbour and distant) sectors, inducing spatially related strategies to ensure water uptake and accompanying cell modification. This information could be critical for understanding how plants maintain and improve their structural integrity—whenever and wherever it is necessary—in natural mechanical stress conditions. [ABSTRACT FROM AUTHOR]

Drought and heat stress substantially impact plant growth and productivity. When subjected to drought or heat stress, plants exhibit reduction in growth resulting in yield losses. The occurrence of these two stresses together intensifies their negative effects. Unraveling the molecular changes in response to combined abiotic stress is essential to breed climate-resilient crops. In this study, transcriptome profiles were compared between stress-tolerant (Otis), and stress-sensitive (Golden Promise) barley genotypes subjected to drought, heat, and combined heat and drought stress for five days during heading stage. The major differences that emerged from the transcriptome analysis were the overall number of differentially expressed genes was relatively higher in Golden Promise (GP) compared to Otis. The differential expression of more than 900 transcription factors in GP and Otis may aid this transcriptional reprogramming in response to abiotic stress. Secondly, combined heat and water deficit stress results in a unique and massive transcriptomic response that cannot be predicted from individual stress responses. Enrichment analyses of gene ontology terms revealed unique and stress type-specific adjustments of gene expression. Weighted Gene Co-expression Network Analysis identified genes associated with RNA metabolism and Hsp70 chaperone components as hub genes that can be useful for engineering tolerance to multiple abiotic stresses. Comparison of the transcriptomes of unstressed Otis and GP plants identified several genes associated with biosynthesis of antioxidants and osmolytes were higher in the former that maybe providing innate tolerance capabilities to effectively combat hostile conditions. Lines with different repertoire of innate tolerance mechanisms can be effectively leveraged in breeding programs for developing climate-resilient barley varieties with superior end-use traits.

Previous studies report that the asymmetric response, observed along the main poplar woody bent root axis, was strongly related to both the type of mechanical forces (compression or tension) and the intensity of force displacement. Despite a large number of targets that have been proposed to trigger this asymmetry, an understanding of the comprehensive and synergistic effect of the antistress spatially related pathways is still lacking. Recent progress in the bioinformatics area has the potential to fill these gaps through the use of in silico studies, able to investigate biological functions and pathway overlaps, and to identify promising targets in plant responses. Presently, for the first time, a comprehensive network-based analysis of proteomic signatures was used to identify functions and pivotal genes involved in the coordinated signalling pathways and molecular activities that asymmetrically modulate the response of different bent poplar root sectors and sides. To accomplish this aim, 66 candidate proteins, differentially represented across the poplar bent root sides and sectors, were grouped according to their abundance profile patterns and mapped, together with their first neighbours, on a high-confidence set of interactions from STRING to compose specific cluster-related subnetworks (I–VI). Successively, all subnetworks were explored by a functional gene set enrichment analysis to identify enriched gene ontology terms. Subnetworks were then analysed to identify the genes that are strongly interconnected with other genes (hub gene) and, thus, those that have a pivotal role in the bent root asymmetric response. The analysis revealed novel information regarding the response coordination, communication, and potential signalling pathways asymmetrically activated along the main root axis, delegated mainly to Ca2+ (for new lateral root formation) and ROS (for gravitropic response and lignin accumulation) signatures. Furthermore, some of the data indicate that the concave side of the bent sector, where the mechanical forces are most intense, communicates to the other (neighbour and distant) sectors, inducing spatially related strategies to ensure water uptake and accompanying cell modification. This information could be critical for understanding how plants maintain and improve their structural integrity—whenever and wherever it is necessary—in natural mechanical stress conditions.

Abstract Genome‐scale studies using high‐throughput sequencing (HTS) technologies generate substantial lists of differentially expressed genes under different experimental conditions. These gene lists need to be further mined to narrow down biologically relevant genes and associated functions in order to guide downstream functional genetic analyses. A popular approach is to determine statistically overrepresented genes in a user‐defined list through enrichment analysis tools, which rely on functional annotations of genes based on Gene Ontology (GO) terms. Here, we propose a new computational approach, GenFam, which allows annotation, classification, and enrichment of genes based on their gene family, thus simplifying identification of candidate gene families and associated genes that may be relevant to the query. GenFam and its integrated database comprises of three hundred and eighty‐four unique gene families and supports gene family analyses for sixty plant genomes. Four comparative case studies with plant species belonging to different clades and families were performed using GenFam which demonstrated its robustness and comprehensiveness over preexisting functional enrichment tools. To make it readily accessible for plant biologists, GenFam is available as a web‐based application where users can input gene IDs and export enrichment results in both tabular and graphical formats. Users can also customize analysis parameters by choosing from the various statistical enrichment tests and multiple testing correction methods. Additionally, the web‐based application, source code, and database are freely available to use and download. Website: https://www.mandadilab.com/genfam/. Source code and database: https://www.mandadilab.com/dload/.

Aging is a complex process that is not yet fully understood. Despite advancements in research, a deeper understanding of the underlying biological mechanisms is necessary to develop interventions that promote healthy longevity. The aim of this study was to elucidate the complex mechanisms associated with healthy aging and longevity in healthy elderly individuals. The RNA sequencing (RNA-seq) data used in this study was obtained from the Gene Expression Omnibus (GEO) database (accession number GSE104406), which was collected from Fluorescent Activated Cell Sorting (FACS) of human bone marrow derived human hematopoietic stem cells (BM-HSCs) (Lineage-, CD34+, CD38-) young (18-30 years old) and aged (65-75 years old) donors who had no known hematological malignancy, with 10 biological replicates per group. The GEO RNA-seq Experiments Interactive Navigator (GREIN) software was used to obtain raw gene-level counts and filtered metadata for this dataset. Next generation knowledge discovery (NGKD) tools provided by BioJupies were used to obtain differentially regulated pathways, gene ontologies (GO), and gene signatures in the BM-HSCs. Finally, the L1000 Characteristic Direction Signature Search Engine (L1000CDS2) tool was used to identify specific drugs that reverse aging-associated gene signatures in old but healthy individuals. The down-regulation of signaling pathways such as longevity regulation, proteasome, Notch, apoptosis, nuclear factor kappa B (NFkB), and peroxisome proliferator-activated receptors (PPAR) signaling pathways in the BM-HSCs of healthy elderly. GO functions related to negative regulation of bone morphogenetic protein (BMP), telomeric DNA binding, nucleoside binding, calcium -dependent protein binding, chromatin-DNA binding, SMAD binding, and demethylase activity were significantly downregulated in the BM-HSCs of the elderly compared to the healthy young group. Importantly, potential drugs such as salermide, celestrol, cercosporin, dorsomorphin dihydrochloride, and LDN-193189 monohydrochloride that can reverse the aging-associated signatures in HSCs from healthy elderly were identified. The analysis of RNA-seq data based on NGKD techniques revealed a plethora of differentially regulated pathways, gene ontologies, and drugs with anti-aging potential to promote healthspan in the elderly., Competing Interests: The author hereby affirms that no connections or involvement with any organization or entity that possesses a financial stake in the topics or materials presented in this manuscript., (© 2024 Biomedical Informatics.)

Thrips transmit one of the most devastating plant viruses worldwide–tomato spotted wilt tospovirus (TSWV). Tomato spotted wilt tospovirus is a type species in the genus Orthotospovirus and family Tospoviridae. Although there are more than 7,000 thrips species, only nine thrips species are known to transmit TSWV. In this study, we investigated the molecular factors that could affect thrips ability to transmit TSWV. We assembled transcriptomes of a vector, Frankliniella fusca [Hinds], and a non-vector, Frankliniella tritici [Fitch], and performed qualitative comparisons of contigs associated with virus reception, virus infection, and innate immunity. Annotations of F. fusca and F. tritici contigs revealed slight differences across biological process and molecular functional groups. Comparison of virus cell surface receptors revealed that homologs of integrin were present in both species. However, homologs of another receptor, heperan sulfate, were present in F. fusca alone. Contigs associated with virus replication were identified in both species, but a contig involved in inhibition of virus replication (radical s-adenosylmethionine) was only present in the non-vector, F. tritici. Additionally, some differences in immune signaling pathways were identified between vector and non-vector thrips. Detailed investigations are necessary to functionally characterize these differences between vector and non-vector thrips and assess their relevance in orthotospovirus transmission. [ABSTRACT FROM AUTHOR]

Peripheral Blood gene expression is widely used in the discovery of biomarkers and development of therapeutics. Recently, a spate of commercial blood collection and preservation systems have been introduced with proprietary variations that may differentially impact the transcriptomic profiles. Comparative analysis of these collection platforms will help optimize protocols to detect, identify, and reproducibly validate true biological variance among subjects. In the current study, we tested two recently introduced whole blood collection methods, RNAgard® and PAXgene® RNA, in addition to the traditional method of peripheral blood mononuclear cells (PBMCs) separated from whole blood and preserved in Trizol reagent. Study results revealed striking differences in the transcriptomic profiles from the three different methods that imply ex vivo changes in gene expression occurred during the blood collection, preservation, and mRNA extraction processes. When comparing the ability of the three preservation methods to accurately capture individuals' expression differences, RNAgard® outperformed PAXgene® RNA, and both showed better individual separation of transcriptomic profiles than PBMCs. Hence, our study recommends using a single blood collection platform, and strongly cautions against combining methods during the course of a defined study. [ABSTRACT FROM AUTHOR]

Multipotent trophoblasts undergo dynamic morphological movement and cellular differentiation after conceptus implantation to generate placenta. However, the mechanism controlling trophoblast development and differentiation during peri-implantation development in human remains elusive. In this study, we modeled human conceptus peri-implantation development from blastocyst to early postimplantation stages by using an in vitro coculture system and profiled the transcriptome of 476 individual trophoblast cells from these conceptuses. We revealed the genetic networks regulating peri-implantation trophoblast development. While determining when trophoblast differentiation happens, our bioinformatic analysis identified T-box transcription factor 3 (TBX3) as a key regulator for the differentiation of cytotrophoblast (CT) into syncytiotrophoblast (ST). The function of TBX3 in trophoblast differentiation is then validated by a loss-of-function experiment. In conclusion, our results provided a valuable resource to study the regulation of trophoblasts development and differentiation during human peri-implantation development. [ABSTRACT FROM AUTHOR]

Objective: Moyamoya disease (MMD) is a chronic occlusive cerebrovascular disease with unknown etiology, sharing many similar clinical symptoms with other vascular disorders. This study aimed to investigate gene dysregulation in peripheral blood of MMD and compare it with other vascular disorders. Methods: Transcriptomic profiles of 12 MMD patients and 8 healthy controls were obtained using RNA sequencing. Differentially expressed genes (DEGs) were identified and several were validated by quantitative real-time PCR in independent samples. Biological pathway enrichment analysis of DEGs and deconvolution of leukocyte subsets in peripheral blood were performed. Expression profiles for other vascular diseases were downloaded from public database and consistent DEGs were calculated. Gene set enrichment analysis (GSEA) was conducted to compare gene dysregulation pattern between MMD and other vascular diseases. Results: A total of 533 DEGs were identified for MMD. Up-regulated genes were mainly involved in extracellular matrix (ECM) organization, whereas down-regulated genes were primarily associated with inflammatory and immune responses. As for cell populations, significantly increased naïve B cells and naïve CD4 cells as well as obviously decreased resting natural killer cells were observed in peripheral blood of MMD patients. GSEA analysis indicated that only up-regulated genes of ischemic stroke and down-regulated genes of coronary artery disease and myocardial infarction were enriched in up-regulated and down-regulated genes of MMD, respectively. Conclusion: Dysregulated genes in peripheral blood of MMD mainly played key roles in ECM organization, inflammatory and immune responses. This gene dysregulation pattern was specific compared with other vascular diseases. Besides, naïve B cells, naïve CD4 cells and resting natural killer cells were aberrantly disrupted in peripheral blood of MMD patients. These results will help elucidate the complicated pathogenic mechanism of MMD. [ABSTRACT FROM AUTHOR]

Background: Environmental and endogenous factors under genetic predisposition are considered to initiate the human intervertebral disc (IVD) degeneration. DNA methylation is an essential mechanism to ensure cell-specific gene expression for normal development and tissue stability. Aberrant epigenetic alterations play a pivotal role in several diseases, including osteoarthritis. However, epigenetic alternations, including DNA methylation, in IVD degeneration have not been evaluated. The purpose of this study was to comprehensively compare the genome-wide DNA methylation profiles of human IVD tissues, specifically nucleus pulpous (NP) tissues, with early and advanced stages of disc degeneration. Methods: Human NP tissues were used in this study. The samples were divided into two groups: early stage degeneration (n = 8, Pfirrmann’s MRI grade: I-III) and advanced stage degeneration (n = 8, grade: IV). Genomic DNA was processed for genome-wide DNA methylation profiling using the Infinium MethylationEPIC BeadChip array. Extraction of raw methylation data, clustering and scatter plot of each group values of each sample were performed using a methylation module in GenomeStudio software. The identification of differentially methylated loci (DMLs) and the Gene Ontology (GO) analysis were performed using R software with the ChAMP package. Results: Unsupervised hierarchical clustering revealed that early and advanced stage degenerated IVD samples segregated into two main clusters by their DNA methylome. A total of 220 DMLs were identified between early and advanced disc degeneration stages. Among these, four loci were hypomethylated and 216 loci were hypermethylated in the advanced disc degeneration stage. The GO enrichment analysis of genes containing DMLs identified two significant GO terms for biological processes, hemophilic cell adhesion and cell-cell adhesion. Conclusions: We conducted a genome-wide DNA methylation profile comparative study and observed significant differences in DNA methylation profiles between early and advanced stages of human IVD degeneration. These results implicate DNA methylation in the process of human IVD degeneration. [ABSTRACT FROM AUTHOR]

Parkinson’s disease (PD) is an irreversible and incurable multigenic neurodegenerative disorder. It involves progressive loss of mid brain dopaminergic neurons in the substantia nigra pars compacta (SN). We compared brain gene expression profiles with those from the peripheral blood cells of a separate sample of PD patients to identify disease-associated genes. Here, we demonstrate the use of gene expression profiling of brain and blood for detecting valid targets and identifying early PD biomarkers. Implementing this systematic approach, we discovered putative PD risk genes in brain, delineated biological processes and molecular functions that may be particularly disrupted in PD and also identified several putative PD biomarkers in blood. 20 of the differentially expressed genes in SN were also found to be differentially expressed in the blood. Further application of this methodology to other brain regions and neurological disorders should facilitate the discovery of highly reliable and reproducible candidate risk genes and biomarkers for PD. The identification of valid peripheral biomarkers for PD may ultimately facilitate early identification, intervention, and prevention efforts as well. [ABSTRACT FROM AUTHOR]

Heart disease is the leading cause of death in the western world. Attaining a mechanistic understanding of human heart development and homeostasis and the molecular basis of associated disease states relies on the use of animal models. Here, we present the cardiac proteomes of 4 model vertebrates with dual circulatory systems: the pig (Sus scrofa), the mouse (Mus musculus), and 2 frogs (Xenopus laevis and Xenopus tropicalis). Determination of which proteins and protein pathways are conserved and which have diverged within these species will aid in our ability to choose the appropriate models for determining protein function and to model human disease. We uncover mammalian- and amphibian-specific, as well as species-specific, enriched proteins and protein pathways. Among these, we find and validate an enrichment in cell-cycle–associated proteins within Xenopus laevis. To further investigate functional units within cardiac proteomes, we develop a computational approach to profile the abundance of protein complexes across species. Finally, we demonstrate the utility of these data sets for predicting appropriate model systems for studying given cardiac conditions by testing the role of Kielin/chordin-like protein (Kcp), a protein found as enriched in frog hearts compared to mammals. We establish that germ-line mutations in Kcp in Xenopus lead to valve defects and, ultimately, cardiac failure and death. Thus, integrating these findings with data on proteins responsible for cardiac disease should lead to the development of refined, species-specific models for protein function and disease states. [ABSTRACT FROM AUTHOR]

The haptophyte alga Emiliania huxleyi is the most abundant coccolithophore in the modern ocean and produces elaborate calcite crystals, called coccolith, in a separate intracellular compartment known as the coccolith vesicle. Despite the importance of biomineralization in coccolithophores, the molecular mechanism underlying it remains unclear. Understanding this precise machinery at the molecular level will provide the knowledge needed to enable further manipulation of biomineralization. In our previous study, altering the calcium concentration modified the calcifying ability of E. huxleyi CCMP371. Therefore in this study, we tested E. huxleyi cells acclimated to three different calcium concentrations (0, 0.1, and 10 mM). To understand the whole transcript profile at different calcium concentrations, RNA-sequencing was performed and used for de novo assembly and annotation. The differentially expressed genes (DEGs) among the three different calcium concentrations were analyzed. The functional classification by gene ontology (GO) revealed that ‘intrinsic component of membrane’ was the most enriched of the GO terms at the ambient calcium concentration (10 mM) compared with the limited calcium concentrations (0 and 0.1 mM). Moreover, the DEGs in those comparisons were enriched mainly in ‘secondary metabolites biosynthesis, transport and catabolism’ and ‘signal transduction mechanisms’ in the KOG clusters and ‘processing in endoplasmic reticulum’, and ‘ABC transporters’ in the KEGG pathways. Furthermore, metabolic pathways involved in protein synthesis were enriched among the differentially expressed proteins. The results of this study provide a molecular profile for understanding the expression of transcripts and proteins in E. huxleyi at different calcium concentrations, which will help to identify the detailed mechanism of its calcification. [ABSTRACT FROM AUTHOR]

Background: The ripening process of olive fruits is associated with chemical and/or enzymatic specific transformations, making them particularly attractive to animals and humans. In olive drupes, including ‘Cassanese’ ones, ripening is usually accompanied by progressive chromatic change, resulting in a final red-brown colourization of both epidermis and mesocarp. This event has an exception in the ‘Leucocarpa’, in which we observed the destabilization in the equilibrium between the chlorophyll metabolism and that of the other pigments, particularly the anthocyanins, whose switch-off during maturation promotes the white colouration of the fruits. Recently, transcription profiling of ‘Leucocarpa’ and ‘Cassanese’ olives along ripening, performed through an Illumina RNA-seq approach, has provided useful insights on gene functions involved in fruit maturation such as those related to the biosynthesis of flavonoids and anthocyanins. Methodology: To assess expression alterations of genes involved in flavonoids and anthocyanins biosynthetic pathways during ripening, possibly caused by small nuclear RNA (snRNA) in olive drupes, snRNA libraries from ‘Leucocarpa’ and ‘Cassanese’ were constructed with RNAs extracted at 100 and 130 Days After Flowering (DAF) and sequenced by an Illumina approach. 130 conserved microRNAs (miRNA) in the Viridiplantae belonging to 14 miRNA families were identified. Regarding the 130 conserved miRNAs, approximately the 48% were identified in all libraries, 5 and 18 miRNAs were shared between the “Cassanese” (C100, C130) and “Leucocarpa” (L100, L130) libraries, respectively. Conclusion: For the remaining reads not-matching with known miRNAs in the Viridiplantae, we combined secondary structure and minimum free energy to discover novel olive miRNAs. Based on these analyses, 492 sequences were considered as putative novel miRNAs. The putative target genes of identified miRNA were computationally predicted by alignment with the olive drupe transcripts obtained from the same samples. A total of 218 transcripts were predicted as targets of 130 known and 492 putative novel miRNAs. Interestingly, some identified target genes are involved in negative regulation of anthocyanin metabolic process. Quantification of the expression pattern of three miRNA and their target transcripts by qRT-PCR assay confirmed the results of Illumina sequencing. [ABSTRACT FROM AUTHOR]

Plant defense responses to biotic stresses are complex biological processes, all governed by sophisticated molecular regulations. Induced systemic resistance (ISR) is one of these defense mechanisms where beneficial bacteria or fungi prime plants to resist pathogens or pest attacks. In ISR, the defense arsenal in plants remains dormant and it is only triggered by an infection, allowing a better allocation of plant resources. Our group recently described that the well-known beneficial bacterium Paraburkholderia phytofirmans PsJN is able to induce Arabidopsis thaliana resistance to Pseudomonas syringae pv. tomato (Pst) DC3000 through ISR, and that ethylene, jasmonate and salicylic acid are involved in this protection. Nevertheless, the molecular networks governing this beneficial interaction remain unknown. To tackle this issue, we analyzed the temporal changes in the transcriptome of PsJN-inoculated plants before and after being infected with Pst DC3000. These data were used to perform a gene network analysis to identify highly connected transcription factors. Before the pathogen challenge, the strain PsJN regulated 405 genes (corresponding to 1.8% of the analyzed genome). PsJN-inoculated plants presented a faster and stronger transcriptional response at 1-hour post infection (hpi) compared with the non-inoculated plants, which presented the highest transcriptional changes at 24 hpi. A principal component analysis showed that PsJN-induced plant responses to the pathogen could be differentiated from those induced by the pathogen itself. Forty-eight transcription factors were regulated by PsJN at 1 hpi, and a system biology analysis revealed a network with four clusters. Within these clusters LHY, WRKY28, MYB31 and RRTF1 are highly connected transcription factors, which could act as hub regulators in this interaction. Concordantly with our previous results, these clusters are related to jasmonate, ethylene, salicylic, acid and ROS pathways. These results indicate that a rapid and specific response of PsJN-inoculated plants to the virulent DC3000 strain could be the pivotal element in the protection mechanism. [ABSTRACT FROM AUTHOR]

RNA-protein interaction plays important roles in post-transcriptional regulation. Recent advancements in cross-linking and immunoprecipitation followed by sequencing (CLIP-seq) technologies make it possible to detect the binding peaks of a given RNA binding protein (RBP) at transcriptome scale. However, it is still challenging to predict the functional consequences of RBP binding peaks. In this study, we propose the Protein-RNA Association Strength (PRAS), which integrates the intensities and positions of the binding peaks of RBPs for functional mRNA targets prediction. We illustrate the superiority of PRAS over existing approaches on predicting the functional targets of two related but divergent CELF (CUGBP, ELAV-like factor) RBPs in mouse brain and muscle. We also demonstrate the potential of PRAS for wide adoption by applying it to the enhanced CLIP-seq (eCLIP) datasets of 37 RNA decay related RBPs in two human cell lines. PRAS can be utilized to investigate any RBPs with available CLIP-seq peaks. PRAS is freely available at . [ABSTRACT FROM AUTHOR]

Notophthalmus viridescens (Red-spotted Newt) possess amazing capabilities to regenerate their organs and other tissues. Previously, using a de novo assembly of the newt transcriptome combined with proteomic validation, our group identified a novel family of five protein members expressed in adult tissues during regeneration in Notophthalmus viridescens. The presence of a putative signal peptide suggests that all these proteins are secretory in nature. Here we employed iterative threading assembly refinement (I-TASSER) server to generate three-dimensional structure of these novel Newt proteins and predicted their function. Our data suggests that these proteins could act as ion transporters, and be involved in redox reaction(s). Due to absence of transgenic approaches in N. viridescens, and conservation of genetic machinery across species, we generated transgenic Drosophila melanogaster to misexpress these genes. Expression of 2775 transcripts were compared between these five newly identified Newt genes. We found that genes involved in the developmental process, cell cycle, apoptosis, and immune response are among those that are highly enriched. To validate the RNA Seq. data, expression of six highly regulated genes were verified using real time Quantitative Polymerase Chain Reaction (RT-qPCR). These graded gene expression patterns provide insight into the function of novel protein family identified in Newt, and layout a map for future studies in the field. [ABSTRACT FROM AUTHOR]

Protein solubility is a critical prerequisite to any proteomics analysis. Combination of urea/thiourea and 3-[(3-cholamidopropyl)dimethylammonio]-1-propanesulfonate (CHAPS) have been routinely used to enhance protein solubilization for oil palm proteomics studies in recent years. The goals of these proteomics analysis are essentially to complement the knowledge regarding the regulation networks and mechanisms of the oil palm fatty acid biosynthesis. Through omics integration, the information is able to build a regulatory model to support efforts in improving the economic value and sustainability of palm oil in the global oil and vegetable market. Our study evaluated the utilization of sodium deoxycholate as an alternative solubilization buffer/additive to urea/thiourea and CHAPS. Efficiency of urea/thiourea/CHAPS, urea/CHAPS, urea/sodium deoxycholate and sodium deoxycholate buffers in solubilizing the oil palm (Elaeis guineensis var. Tenera) mesocarp proteins were compared. Based on the protein yields and electrophoretic profile, combination of urea/thiourea/CHAPS were shown to remain a better solubilization buffer and additive, but the differences with sodium deoxycholate buffer was insignificant. A deeper mass spectrometric and statistical analyses on the identified proteins and peptides from all the evaluated solubilization buffers revealed that sodium deoxycholate had increased the number of identified proteins from oil palm mesocarps, enriched their gene ontologies and reduced the number of carbamylated lysine residues by more than 67.0%, compared to urea/thiourea/CHAPS buffer. Although only 62.0% of the total identified proteins were shared between the urea/thiourea/CHAPS and sodium deoxycholate buffers, the importance of the remaining 38.0% proteins depends on the applications. The only observed limitations to the application of sodium deoxycholate in protein solubilization were the interference with protein quantitation and but it could be easily rectified through a 4-fold dilution. All the proteomics data are available via ProteomeXchange with identifier PXD013255. In conclusion, sodium deoxycholate is applicable in the solubilization of proteins extracted from oil palm mesocarps with higher efficiency compared to urea/thiourea/CHAPS buffer. The sodium deoxycholate buffer is more favorable for proteomics analysis due to its proven advantages over urea/thiourea/CHAPS buffer. [ABSTRACT FROM AUTHOR]

Gene-annotation enrichment is a common method for utilizing ontology-based annotations in gene and gene-product centric knowledgebases. Effective utilization of these annotations requires inferring semantic linkages by tracing paths through edges in the ontological graph, referred to as relations. However, some relations are semantically problematic with respect to scope, necessitating their omission or modification lest erroneous term mappings occur. To address these issues, we created the Gene Ontology Categorization Suite, or GOcats—a novel tool that organizes the Gene Ontology into subgraphs representing user-defined concepts, while ensuring that all appropriate relations are congruent with respect to scoping semantics. Here, we demonstrate the improvements in annotation enrichment by re-interpreting edges that would otherwise be omitted by traditional ancestor path-tracing methods. Specifically, we show that GOcats’ unique handling of relations improves enrichment over conventional methods in the analysis of two different gene-expression datasets: a breast cancer microarray dataset and several horse cartilage development RNAseq datasets. With the breast cancer microarray dataset, we observed significant improvement (one-sided binomial test p-value = 1.86E-25) in 182 of 217 significantly enriched GO terms identified from the conventional path traversal method when GOcats’ path traversal was used. We also found new significantly enriched terms using GOcats, whose biological relevancy has been experimentally demonstrated elsewhere. Likewise, on the horse RNAseq datasets, we observed a significant improvement in GO term enrichment when using GOcat’s path traversal: one-sided binomial test p-values range from 1.32E-03 to 2.58E-44. [ABSTRACT FROM AUTHOR]

Acute hepatopancreatic necrosis disease (AHPND), caused by marine bacteria Vibrio Parahaemolyticus, is a huge problem in shrimp farms. The V. parahaemolyticus infecting material is contained in a plasmid which encodes for the lethal toxins PirABVp, whose primary target tissue is the hepatopancreas, causing sloughing of epithelial cells, necrosis, and massive hemocyte infiltration. To get a better understanding of the hepatopancreas response during AHPND, juvenile shrimp Litopenaeus vannamei were infected by immersion with V. parahaemolyticus. We performed transcriptomic mRNA sequencing of infected shrimp hepatopancreas, at 24 hours post-infection, to identify novel differentially expressed genes a total of 174,098 transcripts were examined of which 915 transcripts were found differentially expressed after comparative transcriptomic analysis: 442 up-regulated and 473 down-regulated transcripts. Gene Ontology term enrichment analysis for up-regulated transcripts includes metabolic process, regulation of programmed cell death, carbohydrate metabolic process, and biological adhesion, whereas for down-regulated transcripts include, microtubule-based process, cell activation, and chitin metabolic process. The analysis of protein- protein network between up and down-regulated genes indicates that the first gene interactions are connected to oxidation-processes and sarcomere organization. Additionally, protein-protein networks analysis identified 20-top highly connected hub nodes. Based on their immunological or metabolic function, ten candidate transcripts were selected to measure their mRNA relative expression levels in AHPND infected shrimp hepatopancreas by RT-qPCR. Our results indicate a close connection between the immune and metabolism systems during AHPND infection. Our RNA-Seq and RT-qPCR data provide the possible immunological and physiological scenario as well as the molecular pathways that take place in the shrimp hepatopancreas in response to an infectious disease. [ABSTRACT FROM AUTHOR]

Background: Circular RNAs (circRNAs) have been shown to interact with microRNAs (miRNA) as competitive endogenous RNAs (ceRNAs) to regulate target gene expression and participate in tumorigenesis. However, the role of circRNA-mediated ceRNAs in bladder cancer (BC) remains unknown. Accordingly, the aim of this study was to elucidate the regulatory mechanisms in BC based on construction of the ceRNA network. Methods: The RNA expression profiles were obtained from public datasets in the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) database, and were used to establish a circRNA-miRNA-mRNA network. The interactions among proteins were analyzed using the STRING database and hubgenes were extracted using the cytoHubba application. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of differentially expressed mRNAs in BC and normal tissue samples were performed to determine the functions of the intersecting mRNAs. Results: A total of 27 circRNAs, 76 miRNAs, and 4744 mRNAs were found to be differentially expressed between BC and normal tissues. The circRNA-miRNA-mRNA ceRNA network was established based on 21 circRNAs, 14 miRNAs, and 150 mRNAs differentially expressed in BC. We also established a protein-protein interaction network and identified 10 hubgenes, which were used to construct circRNA-miRNA-hubgene regulatory modules. The most enriched biological process GO term was strand displacement (P<0.05), and the homologous recombination and Fanconi anemia pathways were significantly enriched (P<0.05) for the differentially expressed genes in BC. Conclusions: We screened several dysregulated circRNAs and established a circRNA-associated ceRNA network by bioinformatics analysis. The identified ceRNAs are likely critical in the pathogenesis of BC and may serve as future therapeutic biomarkers. [ABSTRACT FROM AUTHOR]

Perennial ryegrass (Lolium perenne) is a forage and amenity grass species widely cultivated in temperate regions worldwide. As such, perennial ryegrass populations are exposed to a range of environmental conditions and stresses on a seasonal basis and from year to year. One source of potential stress is limitation on water availability. The ability of these perennial grasses to be able to withstand and recover after periods of water limitation or drought can be a key component of grassland performance. Thus, we were interested in looking at changes in patterns of gene expression associated with increasing water stress. Clones of a single genotype of perennial ryegrass were grown under non-flowering growth room conditions in vermiculite supplemented with nutrient solution. Leaf and root tissue was sampled at 4 times in quadruplicate relating to estimated water contents of 35%, 15%, 5% and 1%. RNA was extracted and RNAseq used to generate transcriptome profiles at each sampling point. Transcriptomes were assembled using the published reference genome sequence and differential gene expression analysed using 3 different programmes, DESeq2, edgeR and limma (with the voom transformation), individually and in combination, deriving Early, Middle and Late stage comparisons. Identified differentially expressed genes were then associated with enriched GO terms using BLAST2GO. For the leaf, up-regulated differentially expressed genes were strongly associated with GO terms only during the Early stage and the majority of GO terms were associated with only down-regulated genes at the Middle or Late stages. For the roots, few differentially expressed genes were identified at either Early or Middle stages. Only one replicate at 1% estimated water content produced high quality data for the root, however, this indicated a high level of differential expression. Again the majority of enriched GO terms were associated with down-regulated genes. The performance of the different analysis programmes and the annotations associated with identified differentially expressed genes is discussed. [ABSTRACT FROM AUTHOR]

In the alcoholic fermentation process, Saccharomyces cerevisiae strains present differences in their nitrogen consumption profiles, these phenotypic outcomes have complex genetic and molecular architectures. In this sense, variations in nitrogen signaling pathways regulated by TORC1 represent one of the main sources of phenotypic diversity in nitrogen consumption. This emphasizes the possible roles that allelic variants from the TORC1 pathway have in the nitrogen consumption differences observed in yeast during the alcoholic fermentation. Here, we studied the allelic diversity in the TORC1 pathway across four yeast strains and determined how these polymorphisms directly impact nitrogen consumption during alcoholic fermentation. Using a reciprocal hemizygosity approach combined with phenotyping under fermentative conditions, we found that allelic variants of GTR1, TOR2, SIT4, SAP185, EAP1, NPR1 and SCH9 underlie differences in the ammonium and amino acids consumption phenotypes. Among these, GTR1 alleles from the Wine/European and West African genetic backgrounds showed the greatest effects on ammonium and amino acid consumption, respectively. Furthermore, we identified allelic variants of SAP185, TOR2, SCH9 and NPR1 from an oak isolate that increased the amino acid consumption preference over ammonium; representing putative candidates coming from a non-domesticated strain that could be used for genetic improvement programs. In conclusion, our results demonstrated that a large number of allelic variants within the TORC1 pathway significantly impacts on regulatory mechanisms of nitrogen assimilation during alcoholic fermentation. [ABSTRACT FROM AUTHOR]

The era of next-generation sequencing has mounted the foundation of many gene expression studies. In rheumatoid arthritis research, this has led to the discovery of important candidate genes which offered novel insights into mechanisms and their possible roles in the cure of the disease. In the last years, data generation has outstripped data analysis and while many studies focused on specific aspects of the disease, a global picture of the disease is not yet accomplished. Here, we analyzed and compared a collection of gene expression information from healthy individuals and from patients suffering under different arthritis conditions from published studies containing the following clinical conditions: early and established rheumatoid arthritis, osteoarthritis and arthralgia. We show comprehensive overviews of this data collection and give new insights specifically on gene expression in the early stage, into sex-dependent gene expression, and we describe general differences in expression of different biotypes of genes. Many genes that are related to cytoskeleton changes (actin filament related genes) are differently expressed in early rheumatoid arthritis in comparison to healthy subjects; interestingly, eight of these genes reverse their expression ratio significantly between men and women compared early rheumatoid arthritis and healthy subjects. There are some slighter changes between men and woman between the conditions early and established rheumatoid arthritis. Another aspect are miRNAs and other gene biotypes which are not only promising candidates for diagnoses but also change their expression grossly in average at rheumatoid arthritis and arthralgia compared to the healthy condition. With a selection of intersecting genes, we were able to generate simple classification models to distinguish between healthy and rheumatoid arthritis as well as between early rheumatoid arthritis to other arthritides based on gene expression. [ABSTRACT FROM AUTHOR]

Protein-protein interaction network data provides valuable information that infers direct links between genes and their biological roles. This information brings a fundamental hypothesis for protein function prediction that interacting proteins tend to have similar functions. With the help of recently-developed network embedding feature generation methods and deep maxout neural networks, it is possible to extract functional representations that encode direct links between protein-protein interactions information and protein function. Our novel method, STRING2GO, successfully adopts deep maxout neural networks to learn functional representations simultaneously encoding both protein-protein interactions and functional predictive information. The experimental results show that STRING2GO outperforms other protein-protein interaction network-based prediction methods and one benchmark method adopted in a recent large scale protein function prediction competition. [ABSTRACT FROM AUTHOR]

Background: It is well known that ruptured intracranial aneurysms are associated with substantial morbidity and mortality, yet our understanding of the genetic mechanisms of rupture remains poor. We hypothesize that applying novel techniques to the genetic analysis of aneurysmal tissue will yield key rupture-associated mechanisms and novel drug candidates for the prevention of rupture. Methods: We applied weighted gene co-expression networks (WGCNA) and population-specific gene expression analysis (PSEA) to transcriptomic data from 33 ruptured and unruptured aneurysm domes. Mechanisms were annotated using Gene Ontology, and gene network/population-specific expression levels correlated with rupture state. We then used computational drug repurposing to identify plausible drug candidates for the prevention of aneurysm rupture. Results: Network analysis of bulk tissue identified multiple immune mechanisms to be associated with aneurysm rupture. Targeting these processes with computational drug repurposing revealed multiple candidates for preventing rupture including Btk inhibitors and modulators of hypoxia inducible factor. In the macrophage-specific analysis, we identify rupture-associated mechanisms MHCII antigen processing, cholesterol efflux, and keratan sulfate catabolism. These processes map well onto several of highly ranked drug candidates, providing further validation. Conclusions: Our results are the first to demonstrate population-specific expression levels and intracranial aneurysm rupture, and propose novel drug candidates based on network-based transcriptomics. [ABSTRACT FROM AUTHOR]

Autophagy-related protein 8 (ATG8) is a highly conserved ubiquitin-like protein that modulates autophagy pathways by binding autophagic membranes and a number of proteins, including cargo receptors and core autophagy components. Throughout plant evolution, ATG8 has expanded from a single protein in algae to multiple isoforms in higher plants. However, the degree to which ATG8 isoforms have functionally specialized to bind distinct proteins remains unclear. Here, we describe a comprehensive protein–protein interaction resource, obtained using in planta immunoprecipitation (IP) followed by mass spectrometry (MS), to define the potato ATG8 interactome. We discovered that ATG8 isoforms bind distinct sets of plant proteins with varying degrees of overlap. This prompted us to define the biochemical basis of ATG8 specialization by comparing two potato ATG8 isoforms using both in vivo protein interaction assays and in vitro quantitative binding affinity analyses. These experiments revealed that the N-terminal β-strand—and, in particular, a single amino acid polymorphism—underpins binding specificity to the substrate PexRD54 by shaping the hydrophobic pocket that accommodates this protein’s ATG8-interacting motif (AIM). Additional proteomics experiments indicated that the N-terminal β-strand shapes the broader ATG8 interactor profiles, defining interaction specificity with about 80 plant proteins. Our findings are consistent with the view that ATG8 isoforms comprise a layer of specificity in the regulation of selective autophagy pathways in plants. [ABSTRACT FROM AUTHOR]

Translucent flash disorder (TFD) is one of the important physiological disorders in mangosteen (Garcinia mangostana L.). TFD has symptoms such as flesh arils that become firm and appear transparent similar to watercore in apple or pear. Information on the changes of gene expression in TFD-affected tissues remain limited, and investigations into the effects of different water regimes still need to be undertaken. Through an RNA sequencing approach using the Ion Proton, 183,274 contigs with length ranging from 173–13,035 bp were constructed by de novo assembly. Functional annotation was analyzed using various public databases such as non-redundant protein NCBI, SwissProt, and Gene Ontology, and KEGG pathway. Our studies compared different water regimes to incidence and differentially expressed genes of TFD-like physiological disorders. From the differentially expressed gene (DEG) between normal air and TFD-affected aril, we identified DEG-related TFD events, which 6228 DEGs in the control condition and 3327 DEGs in under water stress treatment condition remained, and confirmed these with RT-qPCR, including sucrose synthase (SUSY), endoglucanase (GUN), xyloglucan endotransglucosylase/hydrolase (XTH), and polygalacturonase (PG) showed statistically significant. In addition, transcription factors also indicated changes in MYB, NAC and WRKY between tissues and different water regimes. [ABSTRACT FROM AUTHOR]

Comparative gene expression studies are invaluable for predicting how existing genetic pathways may be modified or redeployed to produce novel and variable phenotypes. Fruits are ecologically important organs because of their impact on plant fitness and seed dispersal, modifications in which results in morphological variation across species. A novel fruit type in the Brassicaceae known as heteroarthrocarpy enables distinct dispersal methods in a single fruit through segmentation via a lateral joint and variable dehiscence at maturity. Given the close relationship to Arabidopsis, species that exhibit heteroarthrocarpy are powerful models to elucidate how differences in gene expression of a fruit patterning pathway may result in novel fruit types. Transcriptomes of distal, joint, and proximal regions from Erucaria erucarioides and Cakile lanceolata were analyzed to elucidate within fruit and between species differences in whole transcriptome, gene ontology, and fruit patterning expression profiles. Whole transcriptome expression profiles vary between fruit regions in patterns that are consistent with fruit anatomy. These transcriptomic variances do not correlate with changes in gene ontology, as they remain generally stable within and between both species. Upstream regulators in the fruit patterning pathway, FILAMENTOUS FLOWER and YABBY3, are expressed in the distal and proximal regions of E. erucarioides, but not in the joint, implicating alterations in the pathway in heteroarthrocarpic fruits. Downstream gene, INDEHISCENT, is significantly upregulated in the abscissing joint region of C. lanceolata, which suggests repurposing of valve margin genes for novel joint disarticulation in an otherwise indehiscent fruit. In summary, these data are consistent with modifications in fruit patterning genes producing heteroarthrocarpic fruits through different components of the pathway relative to other indehiscent, non-heteroarthrocarpic, species within the family. Our understanding of fruit development in Arabidopsis is now extended to atypical siliques within the Brassicaceae, facilitating future studies on seed shattering in important Brassicaceous crops and pernicious weeds. [ABSTRACT FROM AUTHOR]

Highbush blueberry (Vaccinium corymbosum) fruit accumulate high levels of anthocyanins during ripening, which might be controlled by abscisic acid (ABA), a signal molecule in non-climacteric fruits. For an integrated view of the ripening process from ABA to anthocyanin biosynthesis, we analyzed the transcriptomes of ‘Bluecrop’ highbush blueberry fruit using RNA-Seq at three ripening stages, categorized based on fruit skin coloration: pale green at ca. 30 days after full bloom (DAFB), reddish purple at ca. 40 DAFB, and dark purple at ca. 50 DAFB. Mapping the trimmed reads against the reference sequences yielded 25,766 transcripts. Of these, 143 transcripts were annotated to encode five ABA biosynthesis enzymes, four ABA signal transduction regulators, four ABA-responsive transcription factors, and 12 anthocyanin biosynthesis enzymes. The analysis of differentially expressed genes between the ripening stages revealed that 11 transcripts, including those encoding nine-cis-epoxycarotenoid dioxygenase, SQUAMOSA-class MADS box transcription factor, and flavonoid 3′,5′-hydroxylase, were significantly up-regulated throughout the entire ripening stages. In fruit treated with 1 g L−1 ABA, at least nine transcripts of these 11 transcripts as well as one transcript encoding flavonoid 3′-hydroxylase were up-regulated, presumably promoting anthocyanin accumulation and fruit skin coloration. These results will provide fundamental information demonstrating that ABA biosynthesis and signal transduction, and anthocyanin biosynthesis are closely associated with anthocyanin accumulation and skin coloration in highbush blueberry fruit during ripening. [ABSTRACT FROM AUTHOR]

Glyphosate is a broad-spectrum herbicide that is used worldwide. It represents a potential harm to surface water, and when commercially mixed with surfactants, its uptake is greatly magnified. The most well-known glyphosate-based product is Roundup. This herbicide is potentially an endocrine disruptor and many studies have shown the cytotoxicity potential of glyphosate-based herbicides. In breast cancer (BC) cell lines it has been demonstrated that glyphosate can induce cellular proliferation via estrogen receptors. Therefore, we aimed to identify gene expression changes in ER+ and ER- BC cell lines treated with Roundup and AMPA, to address changes in canonical pathways that would be related or not with the ER pathway, which we believe could interfere with cell proliferation. Using the Human Transcriptome Arrays 2.0, we identified gene expression changes in MCF-7 and MDA-MB-468 exposed to low concentrations and short exposure time to Roundup Original and AMPA. The results showed that at low concentration (0.05% Roundup) and short exposure (48h), both cell lines suffered deregulation of 11 canonical pathways, the most important being cell cycle and DNA damage repair pathways. Enrichment analysis showed similar results, except that MDA-MB-468 altered mainly metabolic processes. In contrast, 48h 10mM AMPA showed fewer differentially expressed genes, but also mainly related with metabolic processes. Our findings suggest that Roundup affects survival due to cell cycle deregulation and metabolism changes that may alter mitochondrial oxygen consumption, increase ROS levels, induce hypoxia, damage DNA repair, cause mutation accumulation and ultimately cell death. To our knowledge, this is the first study to analyze the effects of Roundup and AMPA on gene expression in triple negative BC cells. Therefore, we conclude that both compounds can cause cellular damage at low doses in a relatively short period of time in these two models, mainly affecting cell cycle and DNA repair. [ABSTRACT FROM AUTHOR]

Disconnected interacting protein 2 homolog A (DIP2A) is highly expressed in nervous system and respiratory system of developing embryos. However, genes regulated by Dip2a in developing brain and lung have not been systematically studied. Transcriptome of brain and lung in embryonic 19.5 day (E19.5) were compared between wild type and Dip2a-/- mice. An average of 50 million reads per sample was mapped to the reference sequence. A total of 214 DEGs were detected in brain (82 up and 132 down) and 1900 DEGs in lung (1259 up and 641 down). GO enrichment analysis indicated that DEGs in both Brain and Lung were mainly enriched in biological processes ‘DNA-templated transcription and Transcription from RNA polymerase II promoter’, ‘multicellular organism development’, ‘cell differentiation’ and ‘apoptotic process’. In addition, COG classification showed that both were mostly involved in ‘Replication, Recombination, and Repair’, ‘Signal transduction and mechanism’, ‘Translation, Ribosomal structure and Biogenesis’ and ‘Transcription’. KEGG enrichment analysis showed that brain was mainly enriched in ‘Thyroid cancer’ pathway whereas lung in ‘Complement and Coagulation Cascades’ pathway. Transcription factor (TF) annotation analysis identified Zinc finger domain containing (ZF) proteins were mostly regulated in lung and brain. Interestingly, study identified genes Skor2, Gpr3711, Runx1, Erbb3, Frmd7, Fut10, Sox11, Hapln1, Tfap2c and Plxnb3 from brain that play important roles in neuronal cell maturation, differentiation, and survival; genes Hoxa5, Eya1, Errfi1, Sox11, Shh, Igf1, Ccbe1, Crh, Fgf9, Lama5, Pdgfra, Ptn, Rbp4 and Wnt7a from lung are important in lung development. Expression levels of the candidate genes were validated by qRT-PCR. Genome wide transcriptional analysis using wild type and Dip2a knockout mice in brain and lung at embryonic day 19.5 (E19.5) provided a genetic basis of molecular function of these genes. [ABSTRACT FROM AUTHOR]

Neutrophil extracellular traps (NET) formation is part of the neutrophil response to infections, but excessive or inappropriate NETosis may trigger the production of autoantibodies and cause organ damage in autoimmune disorders. Spontaneously netting neutrophils are not frequent and induction of NET in vitro by selected stimuli is necessary to investigate their structure. In the present work, the protein composition and post-translational modifications of NET produced under different stimuli have been studied by means of proteomic analysis. Neutrophils from healthy donors were stimulated by PMA, A23187, Escherichia coli LPS or untreated; after three hours, cells were washed, treated with DNase and supernatants collected for mass spectrometry. Data were analyzed by unsupervised hierarchical clustering analyses. We identified proteins contained in NETs of any source or exclusive of one stimulus: LPS-induced and spontaneous NET diverge in protein composition, while PMA- and A23187-induced NET appear more similar. Among the post-translational modifications we examined, methionine sulfoxidation is frequent especially in PMA- and LPS-induced NETs. Myeloperoxidase is the protein more extensively modified. Thus, proteomic analysis indicates that NETs induced by different stimuli are heterogeneous in terms of both protein composition and post-translational modifications, suggesting that NET induced in different conditions may have different biological effects. [ABSTRACT FROM AUTHOR]

Network medicine approaches have been largely successful at increasing our knowledge of molecularly characterized diseases. Given a set of disease genes associated with a disease, neighbourhood-based methods and random walkers exploit the interactome allowing the prediction of further genes for that disease. In general, however, diseases with no known molecular basis constitute a challenge. Here we present a novel network approach to prioritize gene-disease associations that is able to also predict genes for diseases with no known molecular basis. Our method, which we have called Cardigan (ChARting DIsease Gene AssociatioNs), uses semi-supervised learning and exploits a measure of similarity between disease phenotypes. We evaluated its performance at predicting genes for both molecularly characterized and uncharacterized diseases in OMIM, using both weighted and binary interactomes, and compared it with state-of-the-art methods. Our tests, which use datasets collected at different points in time to replicate the dynamics of the disease gene discovery process, prove that Cardigan is able to accurately predict disease genes for molecularly uncharacterized diseases. Additionally, standard leave-one-out cross validation tests show how our approach outperforms state-of-the-art methods at predicting genes for molecularly characterized diseases by 14%-65%. Cardigan can also be used for disease module prediction, where it outperforms state-of-the-art methods by 87%-299%. [ABSTRACT FROM AUTHOR]

The evolutionarily conserved nature of the few well-known anti-aging interventions that affect lifespan, such as caloric restriction, suggests that aging-related research in model organisms is directly relevant to human aging. Since human lifespan is a complex trait, a systems-level approach will contribute to a more comprehensive understanding of the underlying aging landscape. Here, we integrate evolutionary and functional information of normal aging across human and model organisms at three levels: gene-level, process-level, and network-level. We identify evolutionarily conserved modules of normal aging across diverse taxa, and notably show proteostasis to be conserved in normal aging. Additionally, we find that mechanisms related to protein quality control network are enriched for genes harboring genetic variants associated with 22 age-related human traits and associated to caloric restriction. These results demonstrate that a systems-level approach, combined with evolutionary conservation, allows the detection of candidate aging genes and pathways relevant to human normal aging. [ABSTRACT FROM AUTHOR]

Pigeonpea is a major source of dietary protein to the vegetarian population of the Indian sub-continent. Crop improvement to mitigate biotic and abiotic stresses for realization of its potential yield and bridging yield gap is the need of the hour. Availability of limited genomic resources in the cultivated germplasm, however, is a serious bottleneck towards successful molecular breeding for the development of superior genotypes in pigeonpea. In view of this, improvement of pigeonpea can be attempted through transgenesis or by exploiting genetic resources from its wild relatives. Pigeonpea wild relatives are known to be bestowed with agronomic traits of importance; discovery and deployment of genes from them can provide a lucrative option for crop improvement. Understanding molecular signatures of wild relatives would not only provide information about the mechanism behind desired traits but also enable us to extrapolate the information to cultivated pigeonpea. The present study deals with the characterization of leaf transcriptomes of Cajanus cajan and one of its wild relatives, Cajanus platycarpus. Illumina sequencing revealed 0.11 million transcripts in both the species with an annotation of 0.09 million (82%) transcripts using BLASTX. Comparative transcriptome analyses on the whole, divulged cues about the wild relative being vigilant and agile. Gene ontology and Mapman analysis depicted higher number of transcripts in the wild relative pertaining to signaling, transcription factors and stress responsive genes. Further, networking between the differentially expressed MapMan bins demonstrated conspicuous interactions between different bins through 535 nodes (512 Genes and 23 Pathways) and 1857 edges. The authenticity of RNA-seq analysis was confirmed by qRT-PCR. The information emanating from this study can provide valuable information and resource for future translational research including genome editing to alleviate varied stresses. Further, this learning can be a platform for in-depth investigations to decipher molecular mechanisms for mitigation of various stresses in the wild relative. [ABSTRACT FROM AUTHOR]

The developmental pathway of the neural retina (NR) and retinal pigment epithelium (RPE) has been revealed by extensive research in mice. However, the molecular mechanisms underlying the development of the human NR and RPE, as well as the interactions between these two tissues, have not been well defined. Here, we analyzed 2,421 individual cells from human fetal NR and RPE using single-cell RNA sequencing (RNA-seq) technique and revealed the tightly regulated spatiotemporal gene expression network of human retinal cells. We identified major cell classes of human fetal retina and potential crucial transcription factors for each cell class. We dissected the dynamic expression patterns of visual cycle– and ligand-receptor interaction–related genes in the RPE and NR. Moreover, we provided a map of disease-related genes for human fetal retinal cells and highlighted the importance of retinal progenitor cells as potential targets of inherited retinal diseases. Our findings captured the key in vivo features of the development of the human NR and RPE and offered insightful clues for further functional studies. [ABSTRACT FROM AUTHOR]

In systems biology, inference of functional associations among genes is compelling because the construction of functional association networks facilitates biomarker discovery. Specifically, such gene associations in human can help identify putative biomarkers that can be used as diagnostic tools in treating patients. Although biomedical literature is considered a valuable data source for this task, currently only a limited number of webservers are available for mining gene-gene associations from the vast amount of biomedical literature using text mining techniques. Moreover, these webservers often have limited coverage of biomedical literature and also lack efficient and user-friendly tools to interpret and visualize mined relationships among genes. To address these limitations, we developed GAIL (Gene-gene Association Inference based on biomedical Literature), an interactive webserver that infers human gene-gene associations from Gene Ontology (GO) guided biomedical literature mining and provides dynamic visualization of the resulting association networks and various gene set enrichment analysis tools. We evaluate the utility and performance of GAIL with applications to gene signatures associated with systemic lupus erythematosus and breast cancer. Results show that GAIL allows effective interrogation and visualization of gene-gene networks and their subnetworks, which facilitates biological understanding of gene-gene associations. GAIL is available at . [ABSTRACT FROM AUTHOR]

Male sterility (induced or natural) is a potential tool for commercial hybrid seed production in different crops. Despite numerous endeavors to understand the physiological, hereditary, and molecular cascade of events governing CMS in cotton, the exact biological process controlling sterility and fertility reconstruction remains obscure. During current study, RNA-Seq using Ion Torrent S5 platform is carried out to identify ‘molecular portraits’ in floral buds among the Cytoplasmic Genic Male Sterility (CGMS) line, its near-isogenic maintainer, and restorer lines. A total of 300, 438 and 455 genes were differentially expressed in CGMS, Maintainer, and Restorer lines respectively. The functional analysis using AgriGo revealed suppression in the pathways involved in biogenesis and metabolism of secondary metabolites which play an important role in pollen and anther maturation. Enrichment analysis showed dearth related to pollen and anther’s development in sterile line, including anomalous expression of genes and transcription factors that have a role in the development of the reproductive organ, abnormal cytoskeleton formation, defects in cell wall formation. The current study found aberrant expression of DYT1, AMS and cytochrome P450 genes involved in tapetum formation, pollen development, pollen exine and anther cuticle formation associated to male sterility as well as fertility restoration of CGMS. In the current study, more numbers of DEGs were found on Chromosome D05 and A05 as compared to other chromosomes. Expression pattern analysis of fourteen randomly selected genes using qRT-PCR showed high concurrence with gene expression profile of RNA-Seq analysis accompanied by a strong correlation of 0.82. The present study provides an important support for future studies in identifying interaction between cyto-nuclear molecular portraits, to accelerate functional genomics and molecular breeding related to cytoplasmic male sterility studies in cotton. [ABSTRACT FROM AUTHOR]

Gastrointestinal nematodes (GIN) are a major constraint for small ruminant production. Due to the rise of anthelmintic resistance throughout the world, alternative control strategies are needed. The development of GIN resistance breeding programs is a promising strategy. However, a better understanding of the mechanisms underlying genetic resistance might lead to more effective breeding programmes. In this study, we compare transcriptome profiling of abomasal mucosa and lymph node tissues from non-infected, resistant and susceptible infected Creole goats using RNA-sequencing. A total of 24 kids, 12 susceptible and 12 GIN resistant based on the estimated breeding value, were infected twice with 10,000 L3 Haemonchus contortus. Physiological and parasitological parameters were monitored during infection. Seven weeks after the second infection, extreme kids (n = 6 resistant and 6 susceptible), chosen on the basis of the fecal egg counts (FEC), and 3 uninfected control animals were slaughtered. Susceptible kids had significantly higher FEC compared with resistant kids during the second infection with no differences in worm burden, male and female worm count or establishment rate. A higher number of differentially expressed genes (DEG) were identified in infected compared with non-infected animals in both abomasal mucosa (792 DEG) and lymph nodes (1726 DEG). There were fewer DEG in resistant versus susceptible groups (342 and 450 DEG, in abomasal mucosa and lymph nodes respectively). ‘Cell cycle’ and ‘cell death and survival’ were the main identified networks in mucosal tissue when comparing infected versus non-infected kids. Antigen processing and presentation of peptide antigen via major histocompatibility complex class I were in the top biological functions for the DEG identified in lymph nodes. The TGFβ1 gene was one of the top 5 upstream DEG in mucosal tissue. Our results are one of the fist investigating differences in the expression profile induced by GIN infection in goats. [ABSTRACT FROM AUTHOR]

Background: Current laboratory tests are less than 50% accurate in distinguishing between people who have food allergies (FA) and those who are merely sensitized to foods, resulting in the use of expensive and potentially dangerous Oral Food Challenges. This study presents a purely-computational machine learning approach, conducted using DNA Methylation (DNAm) data, to accurately diagnose food allergies and potentially find epigenetic targets for the disease. Methods and results: An unbiased feature-selection pipeline was created that narrowed down 405,000+ potential CpG biomarkers to 18. Machine-learning models that utilized subsets of this 18-feature aggregate achieved perfect classification accuracy on completely hidden test cohorts (on an 8-fold hidden dataset). Ensemble classification was also shown to be effective for this High Dimension Low Sample Size (HDLSS) DNA methylation dataset. The efficacy of these machine learning classifiers and the 18 CpGs was further validated by their high accuracy on a large number of hidden data permutations, where the samples in the training, cross-validation, and hidden sets were repeatedly randomly allocated. The 18-CpG signature mapped to 13 genes, on which biological insights were collected. Notably, many of the FA-discriminating genes found in this study were strongly associated with the immune system, and seven of the 13 genes were previously associated with FA. Conclusions: Previous studies have also created highly-accurate classifiers for this dataset, using both data-driven and a priori biological insights to construct a 96-CpG signature. This research builds on previous work because it uses a completely computational approach to obtain a perfect classification accuracy while using only 18 highly discriminating CpGs (0.005% of the total available features). In machine learning, simpler models, as used in this study, are generally preferred over more complex ones (other things being equal). Lastly, the completely data-driven methodology presented in this research eliminates the need for a priori biological information and allows for generalizability to other DNAm classification problems. [ABSTRACT FROM AUTHOR]

Advances in machine learning and deep learning methods, together with the increasing availability of large-scale pharmacological, genomic, and chemical datasets, have created opportunities for identifying potentially useful relationships within biochemical networks. Knowledge embedding models have been found to have value in detecting knowledge-based correlations among entities, but little effort has been made to apply them to networks of biochemical entities. This is because such networks tend to be unbalanced and sparse, and knowledge embedding models do not work well on them. However, to some extent, the shortcomings of knowledge embedding models can be compensated for if they are used in association with graph embedding. In this paper, we combine knowledge embedding and graph embedding to represent biochemical entities and their relations as dense and low-dimensional vectors. We build a cascade learning framework which incorporates semantic features from the knowledge embedding model, and graph features from the graph embedding model, to score the probability of linking. The proposed method performs noticeably better than the models with which it is compared. It predicted links and entities with an accuracy of 93%, and its average hits@10 score has an average of 8.6% absolute improvement compared with original knowledge embedding model, 1.1% to 9.7% absolute improvement compared with other knowledge and graph embedding algorithm. In addition, we designed a meta-path algorithm to detect path relations in the biomedical network. Case studies further verify the value of the proposed model in finding potential relationships between diseases, drugs, genes, treatments, etc. Amongst the findings of the proposed model are the suggestion that VDR (vitamin D receptor) may be linked to prostate cancer. This is backed by evidence from medical databases and published research, supporting the suggestion that our proposed model could be of value to biomedical researchers. [ABSTRACT FROM AUTHOR]

Avian pathogenic Escherichia coli (APEC) causes great economic loss to the poultry industry worldwide. Chicken type II pneumocytes (CP II cells) secrete surfactants and modulate lung immunity to decrease the infection of the invading pathogen. Nevertheless, the pathogenesis of CP II cells to APEC infection remains poorly understood. Therefore, we conducted global gene expression profiling of CP II cells after APEC-O78 infection to explore the host-pathogen interaction. The differentially expressed genes of CP II cells to APEC infection were characterized by RNA-seq with EB-seq algorithm. In consequence, the mRNA of 18996 genes was identified, and CP II cells responded to APEC infection with marked changes in the expression of 1390 genes. Among them, there are 803 down-regulated mRNAs and 587 up-regulated mRNAs. The KEGG prediction and Gene Ontology terms analysis revealed that the major enriched pathways were related to NF-κB signaling pathway, apoptosis pathway, tight junction, and cytokine-cytokine receptor interaction and other pathways. We adopted qRT-PCR to verify the validity of the selected gene expression. The fold induction of qPCR was similar to the RNA-seq results. These results provide a better understanding of the pathogenesis of APEC, especially apoptosis pathway involved in APEC infection. [ABSTRACT FROM AUTHOR]

Kidney failure occurs in 5–13% of individuals with sickle cell disease and is associated with early mortality. Two APOL1 alleles (G1 and G2) have been identified as risk factors for sickle cell disease nephropathy. Both risk alleles are prevalent in individuals with recent African ancestry and have been associated with nephropathic complications in other diseases. Despite the association of G1 and G2 with kidney dysfunction, the mechanisms by which these variants contribute to increased risk remain poorly understood. Previous work in zebrafish models suggest that the G2 risk allele functions as a dominant negative, whereas the G1 allele is a functional null. To understand better the cellular pathology attributed to APOL1 G2, we investigated the in vivo effects of the G2 risk variant on distinct cell types using RNA sequencing. We surveyed APOL1 G2 associated transcriptomic alterations in podocytes and vascular endothelial cells isolated from zebrafish larvae expressing cell-type specific reporters. Our analysis identified many transcripts (n = 7,523) showing differential expression between APOL1 G0 (human wild-type) and APOL1 G2 exposed podocytes. Conversely, relatively few transcripts (n = 107) were differentially expressed when comparing APOL1 G0 and APOL1 G2 exposed endothelial cells. Pathway analysis of differentially expressed transcripts in podocytes showed enrichment for autophagy associated terms such as “Lysosome” and “Phagosome”, implicating these pathways in APOL1 G2 associated kidney dysfunction. This work provides insight into the molecular pathology of APOL1 G2 nephropathy which may offer new therapeutic strategies for multiple disease contexts such as sickle cell nephropathy. [ABSTRACT FROM AUTHOR]

Chaperone-mediated autophagy (CMA) contributes to the lysosomal degradation of a selective subset of proteins. Selectivity lies in the chaperone heat shock cognate 71 kDa protein (HSC70) recognizing a pentapeptide motif (KFERQ-like motif) in the protein sequence essential for subsequent targeting and degradation of CMA substrates in lysosomes. Interest in CMA is growing due to its recently identified regulatory roles in metabolism, differentiation, cell cycle, and its malfunctioning in aging and conditions such as cancer, neurodegeneration, or diabetes. Identification of the subset of the proteome amenable to CMA degradation could further expand our understanding of the pathophysiological relevance of this form of autophagy. To that effect, we have performed an in silico screen for KFERQ-like motifs across proteomes of several species. We have found that KFERQ-like motifs are more frequently located in solvent-exposed regions of proteins, and that the position of acidic and hydrophobic residues in the motif plays the most important role in motif construction. Cross-species comparison of proteomes revealed higher motif conservation in CMA-proficient species. The tools developed in this work have also allowed us to analyze the enrichment of motif-containing proteins in biological processes on an unprecedented scale and discover a previously unknown association between the type and combination of KFERQ-like motifs in proteins and their participation in specific biological processes. To facilitate further analysis by the scientific community, we have developed a free web-based resource () for direct identification of KFERQ-like motifs in any protein sequence. This resource will contribute to accelerating understanding of the physiological relevance of CMA. [ABSTRACT FROM AUTHOR]

Objectives: The study aimed to investigate the ceRNA network in biological development of Tongue Squamous Cell Carcinoma (TSCC) and to identify novel molecular subtypes of TSCC to screen potential biomarkers for target therapy and prognosis by using integrated genomic analysis based on The Cancer Genome Atlas (TCGA) database. Material and methods: Data on gene expressions were downloaded from TCGA and GEO database. Differentially expressed RNAs(DERNAs) were shown by DESeq2 package in R. Functional enrichment analysis of DEmRNAs was performed using clusterprofilers in R. PPI network was established by referring to String website. Survival analysis of DERNAs was carried out by survival package in R. Interactions among mRNAs, miRNAs and lncRNAs were obtained from Starbase v3.0 and used to construct ceRNA network. Consensus Cluster Plus package was applied to identify molecular subtypes. All key genes were validated by comparing them with GEO microarray data. Statistical analyses of clinical features among different subtypes were performed using SPSS 22.0. Results: A total of 2907 mRNAs (1366 up-regulated and 1541 down-regulated), 191miRNAs (98 up-regulated and 93 down-regulated) and 1831 lncRNAs (1151 up-regulated and 680 down-regulated) were identified from tumor and normal tissues. A ceRNA network was successfully constructed and 15 DEmRNAs, 1 DEmiRNA, 2 DElncRNAs associated with prognosis were employed. Furthermore, we firstly identified 2 molecular subtypes, basal and differentiated, and found that differentiated subtype consumed less alcohol and was related to a better overall survival. Conclusion: The study constructed a ceRNA network and identified molecular subtypes of TSCC, and our findings provided a novel insight into this intractable cancer and potential therapeutic targets and prognostic indicators. [ABSTRACT FROM AUTHOR]

Heterodera glycines (soybean cyst nematode, SCN) is one of the most devastating pathogens of soybean worldwide. The compatible and in compatible interactions between soybean and SCN have well documented. Nevertheless, the molecular mechanism of a nonhost resistant response in soybean against SCN infection remains obscure. Toward this end, a global transcriptional comparison was conducted between susceptible and resistant reactions of soybean roots infected by taking advantage of finding a new pathotype of SCN (SCNT). The soybean cultivar Lee, which exhibits resistant to SCNT and susceptible to HG 1.2.3.4.7 (SCNs) was utilized in the expriments. The results highlighted a nonhost resistant response of soybean. Transcriptome analysis indicated that the number of differentially expressed genes (DEGs) in the resistant interaction (3746) was much larger than that in the susceptible interaction (602). A great number of genes acting as intrinsic component of membrane, integral component of membrane, cell periphery and plasma membrance were remarkably enriched only in the resistant interaction, while the taurine and hypotaurine, phenylpropanoid pathway, plant-pathogen interaction and transcript factors were modulated in both interactions. This is the first study to examine genes expression patterns in a soybean genotype in response to invasion by a virulent and avirulent SCN population at the transcriptional level, which will provide insights into the complicate molecular mechanism of the nonhost resistant interaction. [ABSTRACT FROM AUTHOR]

Background: Gene shaving (GS) is an essential and challenging tools for biomedical researchers due to the large number of genes in human genome and the complex nature of biological networks. Most GS methods are not applicable to non-linear and multi-view data sets. While the kernel based methods can overcome these problems, a well-founded positive definite kernel based GS method has yet to be proposed for biomedical data analysis. Methods and findings: Since the kernel based methods on genomic information can improve the prediction of diseases, here we proposed a noble method, “kernel based gene shaving” which is based on the influence function of kernel canonical correlation analysis. To investigate the performance of the proposed method in comparison to state-of-the-art-method in gene saving, we analyzed extensive simulated and real microarray gene expression data set. The performance metrics including true positive rate, true negative rate, false positive rate, false negative rate, misclassification error rate, the false discovery rate and area under curves were computed for each methods. In colon cancer data analysis, the proposed method identified a significant subsets of 210 genes out of 2000 genes and suggestive superior performance compared with other methods. The proposed method can be applied to the study of other disease process where two view data is a common task. Conclusions: We addressed the challenge of finding unique kernel based GS methods by using the influence function of kernel canonical correlation analysis. The proposed method has shown to have better performance than state-of-the-art-methods in gene saving and has identified many more significant gene interactions, suggesting that genes function in a concerted effort in colon cancer. In similar biomedical data analysis, kernel based methods could be applied to select a potential subset of genes. The positive definite kernel based methods can overcome the non-linearity problem and improve the prediction process. [ABSTRACT FROM AUTHOR]