RNA-seq Analysis

Background Anastrepha fraterculus sp. 1 is considered a quarantine pest in several American countries. Since chemical control applied in an integrated pest management program is the only strategy utilized against this pest, the development of pesticide-free methods, such as the Sterile Insect Technique, is being considered. The search for genes involved in sex-determination and differentiation, and in metabolic pathways associated with communication and mating behaviour, contributes with key information to the development of genetic control strategies. The aims of this work were to perform a comprehensive analysis of A. fraterculus sp. 1 transcriptome and to obtain an initial evaluation of genes associated with main metabolic pathways by the expression analysis of specific transcripts identified in embryos and adults. Results Sexually mature adults of both sexes and 72 h embryos were considered for transcriptome analysis. The de novo transcriptome assembly was fairly complete (62.9%...

Children typically experience more mild symptoms of Coronavirus Disease 2019 (COVID-19) when compared to adults. There is a strong body of evidence that children are also less susceptible to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection with the ancestral viral isolate. However, the emergence of SARS-CoV-2 variants of concern (VOCs) has been associated with an increased number of pediatric infections. Whether this is the result of widespread adult vaccination or fundamental changes in the biology of SARS-CoV-2 remain to be determined. Here, we use primary nasal epithelial cells (NECs) from children and adults, differentiated at an air-liquid interface to show that the ancestral SARS-CoV-2 replicates to significantly lower titers in the NECs of children compared to those of adults. This was associated with a heightened antiviral response to SARS-CoV-2 in the NECs of children. Importantly, the Delta variant also replicated to

Background: Gene expression microarray has been the primary biomarker platform ubiquitously applied in biomedical research, resulting in enormous data, predictive models, and biomarkers accrued. Recently, RNA-seq has looked likely to replace microarrays, but there will be a period where both technologies co-exist. This raises two important questions: Can microarray-based models and biomarkers be directly applied to RNA-seq data? Can future RNA-seq-based predictive models and biomarkers be applied to microarray data to leverage past investment? Results: We systematically evaluated the transferability of predictive models and signature genes between microarray and RNA-seq using two large clinical data sets. The complexity of cross-platform sequence correspondence was considered in the analysis and examined using three human and two rat data sets, and three levels of mapping complexity were revealed. Three algorithms representing different modeling complexity were applied to the three levels of mappings for each of the eight binary endpoints and Cox regression was used to model survival times with expression data. In total, 240,096 predictive models were examined. Conclusions: Signature genes of predictive models are reciprocally transferable between microarray and RNA-seq data for model development, and microarray-based models can accurately predict RNA-seq-profiled samples; while RNA-seq-based models are less accurate in predicting microarray-profiled samples and are affected both by the choice of modeling algorithm and the gene mapping complexity. The results suggest continued usefulness of legacy microarray data and established microarray biomarkers and predictive models in the forthcoming RNA-seq era.

Summary: Unlike DNA, RNA abundances can vary over several orders of magnitude. Thus, identification of RNA–protein binding sites from high-throughput sequencing data presents unique challenges. Although peak identification in ChIP-Seq data has been extensively explored, there are few bioinformatics tools tailored for peak calling on analogous datasets for RNA-binding proteins. Here we describe ASPeak (abundance sensitive peak detection algorithm), an implementation of an algorithm that we previously applied to detect peaks in exon junction complex RNA immunoprecipitation in tandem experiments. Our peak detection algorithm yields stringent and robust target sets enabling sensitive motif finding and downstream functional analyses. Availability: ASPeak is implemented in Perl as a complete pipeline that takes bedGraph files as input. ASPeak implementation is freely available at https://sourceforge.net/projects/as-peak under the GNU General Public License. ASPeak can be run on a personal...

Background: The parasitic flowering plant dwarf mistletoe (Arceuthobium spp., Viscaceae) is one of the most destructive forest pests, posing a major threat to numerous conifer species worldwide. Arceuthobium sichuanense (spruce dwarf mistletoe, SDM) infects Qinghai spruce (Picea crassifolia) and causes severe damage to spruce forests in Northwest China. SDM is a Chinese native parasitic plant and acquires carbohydrates and mineral nutrition from its hosts. However, underlying molecular basis of the physiological development is largely unknown. Investigations of these physiological traits have been hampered by the lack of genomic resources for this species. Results: In this study, to investigate the transcriptomic processes underlying physiological traits and development in SDM, we used RNA from four major tissues (i.e., shoots, flowers, fruits, and seeds) for de novo assembly and to annotate the transcriptome of this species. We uncovered the annotated transcriptome and performed whole genome expression profiling to uncover transcriptional dynamics during physiological development, and we identified key gene categories involved in the process of sexual development. The assembled SDM transcriptome reported in this work contains 331,347 assembled transcripts; 226,687 unigenes were functionally annotated by Gene Ontology analysis. RNA-Seq analysis using this reference transcriptome identified 22,641 differentially expressed genes from shoots, flowers, fruits, and seeds. These genes are enriched in processes including organic substance metabolism, cellular metabolism, biosynthesis, and cellular component. In addition, genes related to transport, transcription, hormone biosynthesis and signaling, carbohydrate metabolism, and photosynthesis were differentially expressed between tissues. This work reveals tissue-specific gene expression patterns and pathways of SDM and implied to a difference between photosynthetic and non-photosynthetic tissues in plants. The data can potentially be used for future investigations on endophytic parasitism and SDM-spruce interaction, and it dramatically increases the available genomic resources for Arceuthobium and dwarf mistletoe communities. This preliminary study of the Arceuthobium transcriptome provides excellent opportunities for characterizing plant parasitic genes with unknown functions.

Phosphate (Pi) deficiency is known to be a major limitation for symbiotic nitrogen fixation (SNF), and hence legume crop productivity globally. However, very little information is available on the adaptive mechanisms, particularly in the important legume crop chickpea (Cicer arietinum L.), which enable nodules to respond to low-Pi availability. Thus, to elucidate these mechanisms in chickpea nodules at molecular level, we used an RNA sequencing approach to investigate transcriptomes of the nodules in Mesorhizobium mediterraneum SWRI9-(MmSWRI9)-chickpea and M. ciceri CP-31-(McCP-31)-chickpea associations under Pi-sufficient and -deficient conditions, of which the McCP-31-chickpea association has a better SNF capacity than the MmSWRI9-chickpea association during Pi starvation. Our investigation revealed that more genes showed altered expression patterns in MmSWRI9-induced nodules than in McCP-31-induced nodules (540 vs. 225) under Pi deficiency, suggesting that the Pi-starvation-more-...

Comprising more than 25 000 species, the Sunflower Family (Compositae or Asteraceae) is the largest family of flowering plants. Many of its lineages have experienced recent and rapid radiations, and the family has a deep and widespread history of large-scale gene duplications and polyploidy. Many of the most important evolutionary questions about the family's diversity remain unanswered due to poor resolution and lack of support for major nodes of the phylogeny. Our group has employed a phylogenomics approach using Hyb-Seq that includes sequencing 1000 low-copy number nuclear markers, plus partial plastomes for large numbers of species. Here we discuss our progress to date and present two phylogenies comprising nine subfamilies and 25 tribes using concatenated and coalescence-based analyses. We discuss future plans for incorporating high-quality reference genomes and transcriptomes to advance systematic and evolutionary studies in the Compositae. While we have made great strides toward developing tools for employing phylogenomics and resolving relationships within Compositae, much work remains. Recently formed global partnerships will work to solve the unanswered evolutionary questions for this megafamily.

We systematically reviewed and meta-analyzed bulk RNA sequencing (RNAseq) studies comparing Alzheimer's disease (AD) patients to controls in human brain tissue. We searched PubMed, Web of Science, and Scopus for human brain bulk RNAseq studies, excluding re-analyses and studies limited to small RNAs or gene panels. We developed 10 criteria for quality assessment and performed a meta-analysis on three high-quality datasets. Of 3266 records, 24 qualified for the systematic review, and one study with three datasets qualified for the meta-analysis. The meta-analysis identified 571 differentially expressed genes (DEGs) in the temporal lobe and 189 in the frontal lobe, including CLU and GFAP. Pathway analysis suggested reactivation of developmental processes in the adult AD brain. Limited data availability constrained the meta-analysis. These findings underscore the need for rigorous methods in AD transcriptomic research to better identify transcriptomic changes and advance biomarker and therapeutic development. This review is registered in PROSPERO (CRD42023466522).

All organisms, fundamentally, are made from the same raw material, namely the elements of the periodic table. Biochemical diversity is achieved with how these elements are utilized, for what purpose and in which physical location. Determining elemental distributions, especially those of trace elements that facilitate metabolism as cofactors in the active centers of essential enzymes, can determine the state of metabolism, the nutritional status or the developmental stage of an organism. Photosynthetic eukaryotes, especially algae, are excellent subjects for quantitative analysis of elemental distribution. These microbes utilize unique metabolic pathways that require various trace nutrients at their core to enable its operation. Photosynthetic microbes also have important environmental roles as primary producers in habitats with limited nutrient supply or toxin contaminations. Accordingly, photosynthetic eukaryotes are of great interest for biotechnological exploitation, carbon sequestration and bioremediation, with many of the applications involving various trace elements and consequently affecting their quota and intracellular distribution. A number of diverse applications were developed for elemental imaging allowing subcellular resolution, with X-ray fluorescence microscopy (XFM) being at the forefront, enabling quantitative descriptions of intact cells in a non-destructive method. This Tutorial Review summarizes the workflow of a quantitative, single-cell elemental distribution analysis of a eukaryotic alga using XFM.

Alternative splicing generates multiple RNA isoforms from a single gene, enriching genetic diversity and impacting gene function. Effective visualization of these isoforms and their expression patterns is crucial but challenging due to limitations in existing tools. Traditional genome browsers lack programmability, while other tools offer limited customization, produce static plots, or cannot simultaneously display structures and expression levels. RNApysoforms was developed to address these gaps by providing a Python-based package that enables concurrent visualization of RNA isoform structures and expression data. Leveraging plotly and polars libraries, it offers an interactive, customizable, and faster-rendering framework suitable for web applications, enhancing the analysis and dissemination of RNA isoform research.

Determining whether the RNA isoforms from medically relevant genes have distinct functions could facilitate direct targeting of RNA isoforms for disease treatment. Here, as a step toward this goal for neurological diseases, we sequenced 12 postmortem, aged human frontal cortices (6 Alzheimer disease cases and 6 controls; 50% female) using one Oxford Nanopore PromethION flow cell per sample. We identified 1,917 medically relevant genes expressing multiple isoforms in the frontal cortex where 1,018 had multiple isoforms with different protein-coding sequences. Of these 1,018 genes, 57 are implicated in brain-related diseases including major depression, schizophrenia, Parkinson’s disease and Alzheimer disease. Our study also uncovered 53 new RNA isoforms in medically relevant genes, including several where the new isoform was one of the most highly expressed for that gene. We also reported on five mitochondrially encoded, spliced RNA isoforms. We found 99 differentially expressed RNA isoforms between cases with Alzheimer disease and controls.

Biological research is increasingly dependent on computational tools, yet many AI models remain opaque or misaligned with domain-specific workflows. Alchemy Bio introduces AI CoPilot, a research assistant designed to interactively support biologists in generating ideas, analyzing literature, and forming hypotheses. Unlike static models, CoPilot is trained on extensive biomedical literature and optimized for real-time collaboration, enabling scientists to test reasoning chains, refine experimental strategies, and co-develop early-stage ideas. This paper outlines CoPilot's design philosophy, use cases, and an open call for domain experts to evaluate its utility across subfields of biology.

Motivation: Single-cell and spatial transcriptomics provide unprecedented insight into diseases. Pharmacotranscriptomic approaches are powerful tools that leverage gene expression data for drug repurposing and discovery. Multiple databases attempt to connect human cellular transcriptional responses to small molecules for use in transcriptome-based drug discovery efforts. However, preclinical research often requires in vivo experiments in non-human species, which makes utilizing such valuable resources difficult. To facilitate both human orthologous conversion of non-human transcriptomes and the application of pharmacotranscriptomic databases to pre-clinical research models, we introduce OrthologAL. OrthologAL interfaces with BioMart to access different gene sets from the Ensembl database, allowing for ortholog conversion without the need for user-generated code. Results: Researchers can input their single-cell or other high-dimensional gene expression data from any species as a Seurat object, and OrthologAL will output a human ortholog-converted Seurat object for download and use. To demonstrate the utility of this application, we tested OrthologAL using single-cell, single-nuclei, and spatial transcriptomic data derived from common preclinical models, including patient-derived orthotopic xenografts of medulloblastoma, and mouse and rat models of spinal cord injury. OrthologAL can convert these data types efficiently to that of corresponding orthologs while preserving the dimensional architecture of the original non-human expression data. OrthologAL will be broadly useful for the simple conversion of Seurat objects and for applying preclinical, high-dimensional transcriptomics data to functional human-derived small molecule predictions.

Canine atopic dermatitis (CAD) is a common allergic skin disease in dogs, associated with a defective epidermal barrier. In this study we investigated the alterations in skin keratinocyte proliferation and differentiation in CAD by quantitative reverse transcription-polymerase chain reaction. Gene expression of keratin (KRT) markers of proliferative and differentiated keratinocytes, together with that of cornified envelope proteins, involucrin (IVL) and filaggrin (FLG), were evaluated. An upregulation of KRT5 and KRT17 in both lesional and non-lesional AD skin was observed (p < 0.05) whereas KRT2e, KRT14, IVL and FLG expression were significantly increased only in lesional AD skin (p < 0.05). Additionally, the expression levels of KRT5, KRT14, KRT17 and IVL in CAD were strongly correlated. In conclusion, the expression of the majority of the studied keratins, as well as IVL and FLG is increased in CAD with close correlation between the proliferative keratins. This is the first report of a correlation of KRT and IVL genes with CAD.

Artificial intelligence (AI) allows for reforming genomics and biomarker exploration through the ability to detect variants, polygenic risk scoring, and integrate multiomics. AI models are excellent for traditional methods because they can perform better in real-time diagnoses and genomic diagnostics. In addition to the so-called "big data" issues regarding data quality, privacy, and model interpretability, newly developed technologies such as federated learning and synthetic data generation propose various solutions for these problems. The main idea is that AI applications in clinical practice can turn precision medicine into personal medicine by achieving a high level of development in personalized treatment strategies for multisystemic diseases.

The analysis of single-cell genomics data creates an intriguing opportunity for researchers to examine the complex biological system more closely but is challenging due to inherent biological and technical noise. One popular approach involves learning a lower dimensional manifold or pseudotime trajectory through the data that can capture the primary sources of variation in the data. A smooth function of pseudotime then can be used to align gene expression patterns through the lineages in the trajectory which later facilitates downstream analysis such as heterogeneous cell type identification. Here, we propose a differential evolution based pseudotime estimation method. The model operates on continuous search space and allows easy integration of the cell capture time information in the inference process. The suitability of the proposed model is investigated by applying it on benchmarking single-cell data sets collected from different organisms using different assaying techniques. The experimental result shows the model's capability of producing plausible biological insights about cell ordering which makes it an appealing choice for pseudoitme estimation using single-cell transcriptome data.

Lysine, butyric acid, and zinc play important roles in skin homeostasis, which involves aging, inflammation, and prevention of skin barrier disruption. This bioactivity spectrum is not replicated by any one topical compound currently in use. Our purpose in this study was to characterize a novel compound, zinc dibutyroyllysinate (ZDL), consisting of zinc with lysine and butyric acid moieties. We used RNA-seq to evaluate its effect on gene expression in a full-thickness skin model. We show that lysine alone has minimal effects on gene expression, whereas ZDL had greater transcriptional bioactivity. The effects of ZDL included an increased expression of genes promoting epidermal differentiation and retinol metabolism, along with a decreased expression of microphthalmia-associated transcription factor (MITF) and other melanogenesis genes. These effects were not replicated by an alternative salt compound (i.e., calcium dibutyroyllysinate). ZDL additionally led to a dose-dependent increase in skin fibroblast extracellular matrix proteins, including collagen I, collagen IV, and prolidase. Loss of melanin secretion was also seen in ZDL-treated melanocytes. These results provide an initial characterization of ZDL as a novel topical agent. Our findings support a rationale for the development of ZDL as a skincare ingredient, with potential applications for diverse conditions, involving melanocyte hyperactivity, pigmentation, inflammation, or aging.

The human placenta is a particular organ that inseparably binds the mother and the fetus. The proper development and survival of the conceptus relies on the essential interplay between maternal and fetal factors involved in cooperation within the placenta. In our study, high-throughput sequencing (RNA-seq) was applied to analyze the global transcriptome of the human placenta during uncomplicated pregnancies. The RNA-seq was utilized to identify the global pattern of the gene expression in placentas (N = 4) from women in single and twin pregnancies. During analyses, we obtained 228,044 transcripts. More than 91% of them were multi-exon, and among them 134 were potentially unknown protein coding genes. Expression levels (FPKM) were estimated for 38,948 transcriptional active regions, and more than 3000 of genes were expressed with FPKM >20 in each sample. Additionally, all unannotated transcripts with estimated FPKM values were localized on the human genome. Highly covered splice junctions unannotated in the human genome (6497) were identified, and among them 30 were novel. To gain a better understanding of the biological implications, the assembled transcripts were annotated with gene ontology (GO) terms. Single nucleotide variants were predicted for the transcripts assigned to each analyzed GO category. Our results may be useful for establishing a general pattern of the gene expression in the human placenta. Characterizing placental transcriptome, which is crucial for a pregnancy's outcome, can serve as a basis for identifying the mechanisms underlying physiological pregnancy, as well as may be useful for an early detection of the genomic defects.

Background Anastrepha fraterculus sp. 1 is considered a quarantine pest in several American countries. Since chemical control applied in an integrated pest management program is the only strategy utilized against this pest, the development of pesticide-free methods, such as the Sterile Insect Technique, is being considered. The search for genes involved in sex-determination and differentiation, and in metabolic pathways associated with communication and mating behaviour, contributes with key information to the development of genetic control strategies. The aims of this work were to perform a comprehensive analysis of A. fraterculus sp. 1 transcriptome and to obtain an initial evaluation of genes associated with main metabolic pathways by the expression analysis of specific transcripts identified in embryos and adults. Results Sexually mature adults of both sexes and 72 h embryos were considered for transcriptome analysis. The de novo transcriptome assembly was fairly complete (62.9%...

Next generation sequencing protocols such as RNA-seq have made the genome wide characterization of the transcriptome a crucial part of many research projects in biology. Analyses of the resulting data provide key information on gene expression and in certain cases on exon or isoform usage. The emergence of transcript quantification software such as Salmon has enabled researchers to efficiently estimate isoform and gene expressions across the genome while tremendously reducing the necessary computational power. Although overall gene expression estimations were shown to be accurate, isoform expression quantifications appear to be a more challenging task. Low expression levels and uneven or insufficient coverage were reported as potential explanations for inconsistent estimates. Here, through the example of the ketohexokinase ( ) gene in mouse, we demonstrate that the use of an incorrect gene Khk annotation can also result in erroneous isoform quantification results. Manual correction ...

Significance Plant leaves are colonized by a complex community of microbes that is shaped by host genetics. Although secreted metabolites are thought to mediate this effect, we investigated whether plants might also secrete RNA that could potentially structure microbial communities via cross-kingdom RNA interference. Here, we report that Arabidopsis leaves are covered with diverse RNAs of plant origin, including abundant tRNAs and tRNAderived fragments. This leaf surface RNA is not associated with extracellular vesicles or protein complexes; however, it is less degraded than RNA found inside the extracellular spaces of leaves, suggesting that leaf surface RNA is secreted directly rather than exuded through stomata or hydathodes. We propose that this RNA plays a direct role in shaping the leaf microbiome.

Accurate prediction of RNA tertiary structure from sequence remains a critical challenge in computational biology. This research explores a hierarchical approach, emphasizing the crucial role of secondary structure prediction as an intermediary step. By accurately identifying secondary structure elements like stem-loops and hairpins, we aim to improve the precision and efficiency of subsequent tertiary structure modeling. We evaluate various machine learning models for secondary structure prediction and investigate their integration with tertiary structure prediction algorithms, demonstrating the potential for significant improvements in overall structural accuracy.

Background Anastrepha fraterculus sp. 1 is considered a quarantine pest in several American countries. Since chemical control applied in an integrated pest management program is the only strategy utilized against this pest, the development of pesticide-free methods, such as the Sterile Insect Technique, is being considered. The search for genes involved in sex-determination and differentiation, and in metabolic pathways associated with communication and mating behaviour, contributes with key information to the development of genetic control strategies. The aims of this work were to perform a comprehensive analysis of A. fraterculus sp. 1 transcriptome and to obtain an initial evaluation of genes associated with main metabolic pathways by the expression analysis of specific transcripts identified in embryos and adults. Results Sexually mature adults of both sexes and 72 h embryos were considered for transcriptome analysis. The de novo transcriptome assembly was fairly complete (62.9%...

Background: In present study we performed whole transcriptome analysis in plaque psoriasis patients and compared lesional skin with non-lesional skin and with the skin from healthy controls. We sequenced total RNA from 12 lesional (LP), 12 non-lesional (NLP) and from 12 normal (C) skin biopsies. Results: Compared with previous gene expression profiling studies we had three groups under analysis -LP, NLP and C. Using NLP samples allows to see the transcriptome of visually normal skin from psoriasis patient. In LP skin S100A12, S100A7A, LCE3E, DEFB4A, IL19 were found up regulated. In addition to already these well-described genes, we also found several other genes related to psoriasis. Namely, KLK9, OAS2, OAS3, PLA2G, IL36G, IL36RN were found to be significantly and consistently related to the psoriatic lesions and this finding is supported also by previous studies. The genes up-regulated in the LP samples were related to the innate immunity, IL17 and IL10 networks. In NLP samples innate immunity and IL17 network were activated, but activation of IL10 network was not evident. The transcriptional changes characteristic in the NLP samples can be considered as a molecular signature of "dormant psoriasis". Conclusions: Taken together, our study described the transcriptome profile characteristic for LP and NLP psoriatic skin. RNA profile of the NLP skin is in between the lesional and healthy skin, with its own specific pattern. We found that both LP and NLP have up-regulated IL17 network, whereas LP skin has up regulated IL10 related cytokines (IL19, IL20, IL24). Moreover, IL36G and IL36RN were identified as strong regulators of skin pathology in both LP and NLP skin samples, with stronger influence in LP samples.

Background: In present study we performed whole transcriptome analysis in plaque psoriasis patients and compared lesional skin with non-lesional skin and with the skin from healthy controls. We sequenced total RNA from 12 lesional (LP), 12 non-lesional (NLP) and from 12 normal (C) skin biopsies. Results: Compared with previous gene expression profiling studies we had three groups under analysis -LP, NLP and C. Using NLP samples allows to see the transcriptome of visually normal skin from psoriasis patient. In LP skin S100A12, S100A7A, LCE3E, DEFB4A, IL19 were found up regulated. In addition to already these well-described genes, we also found several other genes related to psoriasis. Namely, KLK9, OAS2, OAS3, PLA2G, IL36G, IL36RN were found to be significantly and consistently related to the psoriatic lesions and this finding is supported also by previous studies. The genes up-regulated in the LP samples were related to the innate immunity, IL17 and IL10 networks. In NLP samples innate immunity and IL17 network were activated, but activation of IL10 network was not evident. The transcriptional changes characteristic in the NLP samples can be considered as a molecular signature of "dormant psoriasis". Conclusions: Taken together, our study described the transcriptome profile characteristic for LP and NLP psoriatic skin. RNA profile of the NLP skin is in between the lesional and healthy skin, with its own specific pattern. We found that both LP and NLP have up-regulated IL17 network, whereas LP skin has up regulated IL10 related cytokines (IL19, IL20, IL24). Moreover, IL36G and IL36RN were identified as strong regulators of skin pathology in both LP and NLP skin samples, with stronger influence in LP samples.

Cancer is a multigene and widespread disease. Increasing drug resistance leads to the development of new therapeutic targets. Recent research indicates that various cellular components called stress granules (SGs) are engaged in the cancer-related signaling pathway. The phosphoinositol-3-kinase (PI3K)/AKT/mammalian target of rapamycin (mTOR) signaling, considered a master regulator in cancer, has been shown through genomic profiling studies to play a key role in esophageal cancer (EC). In this study, we performed the in silico analysis of an RNA sequencing dataset to investigate the effects of omipalisib, a PI3K/mTOR inhibitor, on EC cell lines. Our objective was to identify novel molecular targets, particularly SG-related proteins, that contribute to drug resistance in EC. Using computational approaches including differential gene expression analysis, pathway analysis, and functional enrichment, we examined the transcriptomic changes in response to omipalisib treatment. Our analysis revealed downregulation of the PI3K/mTOR signaling pathway and upregulation of compensatory pathways such as FOXO and JAK-STAT signaling in response to omipalisib. Notably, we identified 16 SG-related proteins that were significantly upregulated, suggesting their potential role in drug resistance mechanisms. These findings provide new insights into the molecular mechanisms underlying drug resistance in EC and highlight potential novel targets for therapeutic intervention. Currently, EC is limited by the number of potential drugs for treatment and poor prognosis and is prone to chemotherapeutic resistance to existing clinically proven drugs. Our computational analysis offers valuable insights into targeting SGs for cancer drug discovery, potentially enhancing the development of new therapeutic strategies for EC. These results provide a strong foundation for future experimental validation and drug development efforts aimed at overcoming resistance to EC treatment.

The Drosophila species’ 4th chromosome has maintained its heterochromatin properties. The goal of the project was to annotate and understand the regulation of the DNA in heterochromatin environment. We annotated contig 52, part of the 4th chromosome of
species D. ananassae. The contig 52 contains 3 genes: CG33978 (5 isoforms), CG32006, and bip2-PA. The findings of the bip2 gene
annotation showed a disparity between D. ananassae and D. melanogaster species. Although annotating the bip2-PA gene in the
genome browser with the evidence provided by Blastx and the gene record finder did not match with what we observed while annotating
each CDS’s. In D. ananassae, exon#3 is split into two and are transcribed individually. Figure 6 shows D. mel chain evidence for
only one exon but there are two exons based on RNA-seq and RAMPAGE data.

Blind-side hypermelanosis is an emerging concern across the flatfish aquaculture industry including Chinese tongue sole (Cynoglossus semilaevis). Circular RNAs (circRNAs) as endogenous non-coding RNAs have been acknowledged to play important roles in various biological processes. However, the underlying regulatory mechanisms of circRNAs involved in flatfish blind-side hypermelanosis remain unclear. In this study, to profile the circRNA expression pattern and circRNA-microRNA-messenger RNA (mRNA) network, high-throughput sequencing was performed by using blind-side normal and hypermelanotic skins of tongue sole. A total of 73 differentially expressed circRNAs were identified, and the competing endogenous RNA (ceRNA) network was constructed. Furthermore, circRNA host genes and mRNAs involved in ceRNA network were subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes enrichment analyses. Several GO terms and pathways of biological significance were identified and ...

Although the right-handed double helical B-form DNA is most common under physiological conditions, DNA is dynamic and can adopt a number of alternative structures, such as the four-stranded G-quadruplex, left-handed Z-DNA, cruciform and others. Active transcription necessitates strand separation and can induce such non-canonical forms at susceptible genomic sequences. Therefore, it has been speculated that these non-B DNA motifs can play regulatory roles in gene transcription. Such conjecture has been supported in higher eukaryotes by direct studies of several individual genes, as well as a number of large-scale analyses. However, the role of non-B DNA structures in many lower organisms, in particular proteobacteria, remains poorly understood and incompletely documented. In this study, we performed the first comprehensive study of the occurrence of B DNA-non-B DNA transition-susceptible sites (non-B DNA motifs) within the context of the operon structure of the Escherichia coli genome. We compared the distributions of non-B DNA motifs in the regulatory regions of operons with those from internal regions. We found an enrichment of some non-B DNA motifs in regulatory regions, and we show that this enrichment cannot be simply explained by base composition bias in these regions. We also showed that the distribution of several non-B DNA motifs within intergenic regions separating divergently oriented operons differs from the distribution found between convergent ones. In particular, we found a strong enrichment of cruciforms in the termination region of operons; this enrichment was observed for operons with Rho-dependent, as well as Rho-independent terminators. Finally, a preference for some non-B DNA motifs was observed near transcription factor-binding sites. Overall, the conspicuous enrichment of transition-susceptible sites in these specific regulatory regions suggests that non-B DNA structures may have roles in the transcriptional regulation of specific operons within the E. coli genome.

Interleukin-17A, (IL17A) plays a critical role in the development of numerous autoimmune diseases including psoriasis. The clinical success of IL17A neutralizing biologics in psoriasis has underlined its importance as a drug discovery target. While many studies have focused on the differentiation and trafficking of IL17A producing T-helper (Th17) cells, less is known about IL17A-initiated signaling events in stromal and parenchymal cells leading to psoriatic phenotypes. We sought to discover signaling nodes downstream of IL17A contributing to disease pathogenesis. Using IL17A and tumor necrosis factor α (TNF) to stimulate primary human epidermal keratinocytes, we employed two different phenotypic screening approaches. First, a library of ~22,000 annotated compounds was screened for reduced secretion of the pro-inflammatory chemokine IL8. Second, a library of 729 kinases was screened in a pooled format utilizing CRISPR-Cas9 and monitoring IL8 intracellular staining. The highest ranking novel hits identified in both screens were the bromodomain and extra-terminal domain (BET) family proteins, and bromodomain containing protein 2 (BRD2), respectively. Comparison of BRD2, BRD3, and BRD4 silencing with siRNA and CRISPR confirmed that BRD2 was responsible for mediating IL8 production. Pan-BRD inhibitors and BRD2 knockout also reduced IL17A/TNF mediated CXC motif chemokines 1/2/6 (CXCL1/2/6) and granulocyte colony stimulating factor (G-CSF) production. In RNA-Seq analysis, 438 IL17A/TNF dependent genes were reduced in BRD2 deficient primary keratinocytes. KEGG pathway analysis of these genes showed enrichment in TNF signaling and rheumatoid arthritis relevant genes. Moreover, a number of genes important for keratinocyte homeostasis and cornification were dysregulated in BRD2 deficient keratinocytes. In IL17A/TNF/IL22 stimulated 3D organotypic raft cultures, pan-BRD inhibition reduced inflammatory factor production but elicited aberrant cornification, consistent with RNA-Seq analysis. These studies highlight a novel role for BRDs and BRD2 in particular in IL17A-mediated inflammatory signaling.

The red flesh coloration of apples is a result of a biochemical pathway involved in the biosynthesis of anthocyanins and anthocyanidins. Based on apple genome analysis, a high number of regulatory genes, mainly transcription factors such as MYB, which are components of regulatory complex MYB-bHLH-WD40, and several structural genes (PAL, 4CL, CHS, CHI, F3H, DFR, ANS, UFGT) involved in anthocyanin biosynthesis, have been identified. In this study, we investigated novel genes related to the red-flesh apple phenotype. These genes could be deemed molecular markers for the early selection of new apple cultivars. Based on a comparative transcriptome analysis of apples with different fruit-flesh coloration, we successfully identified and characterized ten potential genes from the plant hormone transduction pathway of auxin (GH3); cytokinins (B-ARR); gibberellins (DELLA); abscisic acid (SnRK2 and ABF); brassinosteroids (BRI1, BZR1 and TCH4); jasmonic acid (MYC2); and salicylic acid (NPR1). An analysis of expression profiles was performed in immature and ripe fruits of red-fleshed cultivars. We have uncovered genes mediating the regulation of abscisic acid, salicylic acid, cytokinin, and jasmonic acid signaling and described their role in anthocyanin biosynthesis, accumulation, and degradation. The presented results underline the relationship between genes from the hormone signal transduction pathway and UFGT genes, which are directly responsible for anthocyanin color transformation as well as anthocyanin accumulation during apple-fruit ripening.

SCARB1 is an important gene for carotenoid functioning and maintaining body color. In this study, we examined wild red (SCARB1 +/+), mutant red (SCARB1 − /+), and mutant white (SCARB1 − /−) fish to investigate changes in gene expression and metabolic processes using skin transcriptomics and blood metabolomics in Oujiang color common carp, Cyprinus carpio var. color. According to our findings, 85 and 30 genes for lipid transport and metabolism and 12 and 4 genes for retinol metabolism were significantly differentially expressed (DE) respectively between the comparison of pairs SCARB1 − /− vs SCARB1 +/+ and SCARB1 − /− vs SCARB1 − /+. Besides, 6 metabolites for lipid transport and metabolism and 1 metabolite for retinol metabolism were significantly DE in SCARB1 − /− vs SCARB1 +/+ pair comparison. Analysis of data from multiple omics systems revealed significant changes in metabolic pathways, including statin, lipid, and carotenoid pathways. Notably, downregulation in gene expression and blood metabolite levels was observed in the glycerophospholipid and retinol metabolic pathways in SCARB1 − /− fish as a result of the SCARB1 gene knock out. Down-regulated genes such as dgkA, CYP27C1, and the L-serine, and 4-Oxoretinol metabolites of the glycerophospholipid and retinol metabolic pathway are likely to regulate the pigmentation mechanism and carotenoid production in the skin cells of SCARB1 − /− fish. Our investigation into the effects of SCARB1 gene knock out has yielded valuable insights into carotenoid functioning and integrated networks. This information contributes to further research on the molecular mechanisms underlying carotenoid functioning and its correlation with genes related to the SCARB1 gene.

Introduction: An important strategy to combat yield loss challenge is the development of varieties with increased tolerance to drought to maintain production. Improvement of crop yield under drought stress is critical to global food security. Methods: In this study, we performed multiomics analysis in a collection of 119 diverse rapeseed (Brassica napus L.) varieties to dissect the genetic control of agronomic traits in two watering regimes [well-watered (WW) and drought stress (DS)] for 3 years. In the DS treatment, irrigation continued till the 50% pod development stage, whereas in the WW condition, it was performed throughout the whole growing season. Results: The results of the genome-wide association study (GWAS) using 52,157 single-nucleotide polymorphisms (SNPs) revealed 1,281 SNPs associated with traits. Six stable SNPs showed sequence variation for flowering time between the two irrigation conditions across years. Three novel SNPs on chromosome C04 for plant weight were located within drought tolerance-related gene ABCG16, and their pleiotropically effects on seed weight per plant and seed yield were characterized. We identified the C02 peak as a novel signal for flowering time, harboring 52.77% of the associated SNPs. The 288-kbps LD decay distance analysis revealed 2,232 candidate genes (CGs) associated with traits. The CGs BIG1-D, CAND1, DRG3, PUP10, and PUP21 were involved in phytohormone signaling and pollen development with significant effects on seed number, seed weight, and grain yield in drought conditions. By integrating GWAS and RNA-seq, 215 promising CGs were Frontiers in Plant Science frontiersin.org 01

Several studies have demonstrated that ultraviolet-band-C (UV-C) irradiation can en-hance plants’ natural resistance to pathogens and diseases. A suitable dose of UV-C radiation in-duces the production of metabolites that strengthen plant defenses , an effect known as "hormesis". Hormesis presents a promising alternative to supplement and reduce the use of pesticides, which pose risks to the environment and human health. This paper investigates the effects of UV-C radiation emitted by an array of Light Emitting Diodes (LEDs) in generating a hormetic response in three kiwifruit species, namely A. chinensis var. deliciosa cv. Hayward, A. chinensis var. chinensis cv. Soreli® and A. arguta plantlets, grown in vitro and in pot, exposed to the pathogen Pseudomonas syringae pv. actinidiae (Psa) either before or after UV-C irradiation. Analyses of morpho-physiological parameter and spectrophotometric assays were conducted to evaluate changes in chlorophyll a and b content, carotenoids, total phenols, and antioxidant activity as a function of the UV-C irradiation. Results indicate partial protection against Psa infection and increased levels of chlorophylls, carotenoids, polyphenols and antioxidant activity. The optimal UV-C dose was determined to be 2.2 kJ/m2 for in vitro shoots and 1.3 kJ/m2 ,for ex vitro plants.

Autophagy contributes to reorganizing intracellular components and forming fat droplets during the adipocyte differentiation. Here, we systematically describe the role of autophagy-related genes and gene sets during the differentiation of adipocytes. We used a public dataset from the European Nucleotide Archive from an RNA-seq experiment in which 3T3-L1 cells were induced by a differentiation induction medium, total RNA was extracted and sequenced at four different time points. Raw reads were aligned to the UCSC mouse reference genome (mm10) using HISAT2, and aligned reads were summarized at the gene or exon level using HTSeq. DESeq2 and DEXSeq were used to model the gene and exon counts and test for differential expression and relative exon usage, respectively. After applying the appropriate transformation, gene counts were used to perform the gene set and pathway enrichment analysis. Data were obtained, processed and annotated using R and Bioconductor. Several autophagy-related ge...

The oomycete Phytophthora palmivora infects the fruit of cacao trees (Theobroma cacao) causing black pod rot and reducing yields. Cacao genotypes vary in their resistance levels to P. palmivora, yet our understanding of how cacao fruit respond to the pathogen at the molecular level during disease establishment is limited. To address this issue, disease development and RNA-Seq studies were conducted on pods of seven cacao genotypes (ICS1, WFT, Gu133, Spa9, CCN51, Sca6 and Pound7) to better understand their reactions to the post-penetration stage of P. palmivora infection. The pod tissue-P. palmivora pathogen assay resulted in the genotypes being classified as susceptible (ICS1, WFT, Gu133 and Spa9) or resistant (CCN51, Sca6 and Pound7). The number of differentially expressed genes (DEGs) ranged from 1625 to 6957 depending on genotype. A custom gene correlation approach identified 34 correlation groups. De novo motif analysis was conducted on upstream promoter sequences of differentially expressed genes, identifying 76 novel motifs, 31 of which were overrepresented in the upstream sequences of correlation groups and associated with gene ontology terms related to oxidative stress response, defense against fungal pathogens, general metabolism and cell function. Genes in one correlation group (Group 6) were strongly induced in all genotypes and enriched in genes annotated with defense-responsive terms. Expression pattern profiling revealed that genes in Group 6 were induced to higher levels in the resistant genotypes. An additional analysis allowed the identification of 17 candidate cis-regulatory modules likely to be involved in cacao defense against P. palmivora. This study is a comprehensive exploration of the cacao pod transcriptional response to P. palmivora spread after infection. We identified cacao genes, promoter motifs, and promoter motif combinations associated with post-penetration resistance to P. palmivora in cacao pods and provide this information as a resource to support future and ongoing efforts to breed P. palmivora-resistant cacao. Cacao (Theobroma cacao L.) farms are affected by black pod rot (BPR), a devastating disease caused by multiple Phytophthora species, among which Phytophthora palmivora (Ppal) is the most widespread 1 . Ppal attacks all cacao parts, including pods, leaves, stems and branches, but is most damaging on pods 2 . Cacao pods are harvested at maturity for their seeds, commonly known as cocoa beans, which are processed to make chocolate. Estimates of cacao fruit yield losses due to Phytopthora diseases are approximately 30%, or 3.8 billion USD in value 3 . Early studies into cacao resistance to BPR explored the differential responses of cacao in response to different inoculations and inoculum sources 4 . This early work led to the discovery that cacao polyphenol oxidase activity was an important component of the Ppal resistance response 5 . Inoculation methods were later developed to distinguish the two distinct stages of infection: the penetration stage and the post-penetration stage 6 . In

Bacterial endosymbionts are highly prevalent among invertebrate animals, in which they can confer fitness benefits such as pathogen defence and/or act as reproductive manipulators, inducing phenotypes including cytoplasmic incompatibility (CI). For the alpha- proteobacterium Wolbachia, its wide distribution among macroparasites and disease- transmitting arthropods coupled with mutualistic roles, reduction of vector competence, and CI have found recent applications in the control of several vector-borne tropical diseases. However, in common with other bacterial endosymbionts, which often lose regulatory elements during genomic erosion, the degree to which Wolbachia can respond to environmental or pharmacological stressors is poorly understood. Here, we apply Cappable- Seq methodology to achieve unprecedented depth and resolution of transcriptional start sites (TSS) in two Wolbachia strains (wMelPop-CLA and wAlbB) that have been used to transinfect mosquitoes for arbovirus control. We exposed Wolbachia in mosquito cell lines to temperature stress (both strains) or antibiotics (wAlbB only) and observed that all classes of TSS (including antisense) exhibited differential regulation, some of which were associated with mobile elements and may control ncRNA expression. Cappable-Seq also resolved the organisation of the bicistronic cifA/cifB operon that is responsible for inducing CI in Wolbachia hosts and shows great promise for revealing regulation of symbiont functions in whole invertebrates.

IL-36 cytokines have recently emerged as mediators of inflammation in autoimmune conditions including psoriasis vulgaris (PsV) and generalized pustular psoriasis (GPP). This study used RNA-seq to profile the transcriptome of primary epidermal keratinocytes (KCs) treated with IL-1B, IL-36A, IL-36B, or IL-36G. We identified some early IL-1B-specific responses (8 h posttreatment), but nearly all late IL-1B responses were replicated by IL-36 cytokines (24 h posttreatment). Type I and II interferon genes exhibited time-dependent response patterns, with early induction (8 h) followed by no response or repression (24 h). Altogether, we identified 225 differentially expressed genes (DEGs) with shared responses to all 4 cytokines at both time points (8 and 24 h). These involved upregulation of ligands (, and) and activating proteases () but also upregulation of inhibitors such asand. Shared IL-1B/IL-36 DEGs overlapped significantly with genes altered in PsV and GPP skin lesions, as well as g...

Ischaemic mitral regurgitation (IMR), a frequent complication following myocardial infarction (MI), leads to higher mortality and poor clinical prognosis if untreated. Accumulating evidence suggests that mitral valve (MV) leaflets actively remodel post MI, and this remodelling increases both the severity of IMR and the occurrence of MV repair failures. However, the mechanisms of extracellular matrix maintenance and modulation by MV interstitial cells (MVICs) and their impact on MV leaflet tissue integrity and repair failure remain largely unknown. Herein, we sought to elucidate the multiscale behaviour of IMR-induced MV remodelling using an established ovine model. Leaflet tissue at eight weeks post MI exhibited significant permanent plastic radial deformation, eliminating mechanical anisotropy, accompanied by altered leaflet composition. Interestingly, no changes in effective collagen fibre modulus were observed, with MVICs slightly rounder, at eight weeks post MI. RNA sequencing i...

The application of artificial intelligence (AI) in bioinformatics has shown promising advancements in genomics and proteomics. This study evaluates the performance of convolutional neural networks (CNNs), recurrent neural networks (RNNs), and support vector machines (SVMs) in gene prediction, protein structure prediction, and functional annotation tasks. Our CNN model achieved a remarkable accuracy of 98.5% in predicting gene regions, significantly outperforming the traditional hidden Markov model (HMM) with an accuracy of 91.2%. For protein structure prediction, the RNN model attained a Q3 accuracy of 85.7%, surpassing the 78.4% accuracy of homology modeling methods. The SVM model used for functional annotation of proteins achieved an F1 score of 0.76, compared to 0.68 for a nearest-neighbor approach. These results underscore the superior performance of AI models in bioinformatics, highlighting their potential to revolutionize genomic and proteomic research. Future work should focus on integrating multi-omics data, improving model interpretability, and enhancing computational efficiency. This study demonstrates that AI can significantly enhance the accuracy and efficiency of bioinformatics analyses, paving the way for new insights and applications in the field.

Pseudomonas cichorii is an economically important pathogen which infects many vegetables and ornamentals worldwide. In spite of many studies to understand the underlying mechanisms in virulence of Pseudomonas spp, the function of srf cluster including srfC, which is formerly known as HopL1, a type 3 effecter protein remains an enigma in plant pathology. In this study, we knocked out srfA, srfB, srfC, and srfD genes from the srf cluster of P. cichorii JBC1 (JBC1) individually to study their role in the virulence and life style of the patho-gen. When we performed seedling-flood inoculation assay using tomato seed-lings, we observed significant reduction in disease symptoms in the seedlings infected with △srfC strain compared with those infected with complemented strain (△srfC::psrfC), △srfA, △srfB and, △srfD strains which exhibited severe symp-toms as that of the JBC1 strain. Subsequently, we infected mature tomato plants by dipping inoculation with bacterial suspensions of △srfC, △sr...

Research Paper Plant phenolic monoterpenes, such as thymol and carvacrol, have a wide range of applications in medicinal, pharmaceutical and other industries. Ajowan is an aromatic medicinal plant from the Apiaceae family with thymol as an active component of its seeds. The seeds of ajowan are valuable for medicinal purposes because their essential oil contains active substances of thymol, carvacrol, γ-terpinene, and p-cymene. Cytochrome P450 (CYP)-related genes have an indispensable role in the biosynthetic pathway of thymol and other substances in ajowan. A cytochrome P450 gene (CYP71D500) with a high expression level was isolated from the ajowan, cloned and sequenced. The sequencing information from the previous RNA-Seq study confirmed that the isolated gene belongs to the plant CYP71 clan, with a 1654 bp length containing two exons and a 115 bp intron. The full-length cDNA of CYP71D500 was also cloned. The sequencing of CYP71D500 cDNA showed the complete homology of CYP71D500 cDNA and exon regions of the CYP71D500 genomic sequence. The sequencing analysis of CYP71D500 cDNA also revealed a mutation that changed isoleucine to valine amino acid. The 3D structural analysis of the enzyme showed that the modified amino acid is not located in the enzyme's active site. Therefore, this cannot probably affect the synthesis of thymol. The isolated gene and cDNA could be used for the metabolic engineering of ajowan and other medicinal plants with active phenolic monoterpenes. It is also applicable for identifying the different functions of the cloned CYP gene in ajowan or other medicinal plants.

Background: Single-cell transcriptome (SCT) sequencing technology has reached the level of high-throughput technology where gene expression can be measured concurrently from large numbers of cells. The results of gene expression studies are highly reproducible when strict protocols and standard operating procedures (SOP) are followed. However, differences in sample processing conditions result in significant changes in gene expression profiles making direct comparison of different studies difficult. Unsupervised machine learning (ML) uses clustering algorithms combined with semi-automated cell labeling and manual annotation of individual cells. They do not scale up well and a workflow used on a specific dataset will not perform well with other studies. Supervised ML classification shows superior classification accuracy and generalization properties as compared to unsupervised ML methods. We describe a supervised ML method that deploys artificial neural networks (ANN), for 5-class classification of healthy peripheral blood mononuclear cells (PBMC) from multiple diverse studies. Results: We used 58 data sets to train ANN incrementally-over ten cycles of training and testing. The sample processing involved four protocols: separation of PBMC, separation of PBMC + enrichment (by negative selection), separation of PBMC + FACS, and separation of PBMC + MACS. The training data set included between 85 and 110 thousand cells, and the test set had approximately 13 thousand cells. Training and testing were done with various combinations of data sets from four principal data sources. The overall accuracy of classification on independent data sets reached 5-class classification accuracy of 94%. Classification accuracy for B cells, monocytes, and T cells exceeded 95%. Classification accuracy of natural killer (NK) cells was 75% because of the similarity between NK cells and T cell subsets. The accuracy of dendritic cells (DC) was low due to very low numbers of DC in the training sets. Conclusions: The incremental learning ANN model can accurately classify the main types of PBMC. With the inclusion of more DC and resolving ambiguities between T cell and NK cell gene expression profiles, we will enable high accuracy supervised ML classification of PBMC. We assembled a reference data set for healthy PBMC and demonstrated a proof-of-concept for supervised ANN method in classification of previously unseen SCT data. The classification shows high accuracy, that is consistent across different studies and sample processing methods.

The post-transcriptional processing and chemical modification of HIV RNA are understudied aspects of HIV virology, primarily due to the limited ability to accurately map and quantify RNA modifications. Modification-specific antibodies or modification-sensitive endonucleases coupled with short-read RNA sequencing technologies have allowed for low-resolution or limited mapping of important regulatory modifications of HIV RNA such as N6-methyladenosine (m6A). However, a high-resolution map of where these sites occur on HIV transcripts is needed for detailed mechanistic understanding. This has recently become possible with new sequencing technologies. Here, we describe the direct RNA sequencing of HIV transcripts using an Oxford Nanopore Technologies sequencer and the use of this technique to map m6A at near single nucleotide resolution. This technology also provides the ability to identify splice variants with long RNA reads and thus, can provide high-resolution RNA modification maps that distinguish between overlapping splice variants. The protocols outlined here for m6A also provide a powerful paradigm for studying any other RNA modifications that can be detected on the nanopore platform.

De novo assemblies do not have the possibility of quality control with an external sequence. In fact, accuracy and reliability of these assemblies is highly affected by sequencing errors and mis-assemblies. Here, a frequency- based algorithm is developed in Ruby and intended to discern assembly errors from polymorphisms/read errors and then edit or remove the misassembled read(s) to provide more but highly reliable contigs. The software reads and writes the ACE assembly format. Transcriptome and genome assemblies were tested.

Background: Low iron bioavailability is a common feature of ocean surface water and therefore micro-algae developed original strategies to optimize iron uptake and metabolism. The marine picoeukaryotic green alga Ostreococcus tauri is a very good model for studying physiological and genetic aspects of the adaptation of the green algal lineage to the marine environment: it has a very compact genome, is easy to culture in laboratory conditions, and can be genetically manipulated by efficient homologous recombination. In this study, we aimed at characterizing the mechanisms of iron assimilation in O. tauri by combining genetics and physiological tools. Specifically, we wanted to identify and functionally characterize groups of genes displaying tightly orchestrated temporal expression patterns following the exposure of cells to iron deprivation and day/night cycles, and to highlight unique features of iron metabolism in O. tauri, as compared to the freshwater model alga Chalamydomonas reinhardtii. Results: We used RNA sequencing to investigated the transcriptional responses to iron limitation in O. tauri and found that most of the genes involved in iron uptake and metabolism in O. tauri are regulated by day/night cycles, regardless of iron status. O. tauri lacks the classical components of a reductive iron uptake system, and has no obvious iron regulon. Iron uptake appears to be copper-independent, but is regulated by zinc. Conversely, iron deprivation resulted in the transcriptional activation of numerous genes encoding zinc-containing regulation factors. Iron uptake is likely mediated by a ZIP-family protein (Ot-Irt1) and by a new Fea1-related protein (Ot-Fea1) containing duplicated Fea1 domains. The adaptation of cells to iron limitation involved an iron-sparing response tightly coordinated with diurnal cycles to optimize cell functions and synchronize these functions with the day/ night redistribution of iron orchestrated by ferritin, and a stress response based on the induction of thioredoxin-like proteins, of peroxiredoxin and of tesmin-like methallothionein rather than ascorbate. We briefly surveyed the metabolic remodeling resulting from iron deprivation. Conclusions: The mechanisms of iron uptake and utilization by O. tauri differ fundamentally from those described in C. reinhardtii. We propose this species as a new model for investigation of iron metabolism in marine microalgae.

Chronic exposure of pancreatic β-cells to elevated nutrient levels impairs their function and potentially induces apoptosis. Like in other cell types, AMPK is activated in β-cells under conditions of nutrient deprivation, while little is known on AMPK responses to metabolic stresses. Here, we first reviewed recent studies on the role of AMPK activation in β-cells. Then, we investigated the expression profile of AMPK pathways in β-cells following metabolic stresses. INS-1E β-cells and human islets were exposed for 3 days to glucose (5.5–25 mM), palmitate or oleate (0.4 mM), and fructose (5.5 mM). Following these treatments, we analyzed transcript levels of INS-1E β-cells by qRT-PCR and of human islets by RNA-Seq; with a special focus on AMPK-associated genes, such as the AMPK catalytic subunits α1 (Prkaa1) and α2 (Prkaa2). AMPKα and pAMPKα were also evaluated at the protein level by immunoblotting. Chronic exposure to the different metabolic stresses, known to alter glucose-stimulate...

Repair and regeneration are key processes for tissue maintenance, and their disruption may lead to disease states. Little is known about the molecular mechanisms that underline the repair and regeneration of the digestive tract. The sea cucumber Holothuria glaberrima represents an excellent model to dissect and characterize the molecular events during intestinal regeneration. To study the gene expression profile, cDNA libraries were constructed from normal, 3-day, and 7-day regenerating intestines of H. glaberrima. Clones were randomly sequenced and queried against the nonredundant protein database at the National Center for Biotechnology Information. RT-PCR analyses were made of several genes to determine their expression profile during intestinal regeneration. A total of 5,173 sequences from three cDNA libraries were obtained. About 46.2, 35.6, and 26.2% of the sequences for the normal, 3-days, and 7-days cDNA libraries, respectively, shared significant similarity with known sequences in the protein database of GenBank but only present 10% of similarity among them. Analysis of the libraries in terms of functional processes, protein domains, and most common sequences suggests that a differential expression profile is taking place during the regeneration process. Further examination of the expressed sequence tag dataset revealed that 12 putative genes are differentially expressed at significant level (R Ͼ 6). Experimental validation by RT-PCR analysis reveals that at least three genes (unknown C-4677-1, melanotransferrin, and centaurin) present a differential expression during regeneration. These findings strongly suggest that the gene expression profile varies among regeneration stages and provide evidence for the existence of differential gene expression. intestine; cDNA libraries; echinoderm EACH YEAR, 60 million to 70 million people are affected by digestive diseases, and over 234,000 deaths, including those from gastrointestinal cancers, are registered (2, 42). Many of the digestive diseases are due to malfunctions of intestinal cell growth and repair mechanisms (28). When the repair of the mucosal epithelium is disturbed, as occurs in diseases such as inflammatory bowel disease or chronic colitis, persistent ulcer lesions can appear (40). Another example is a series of digestive system diseases caused by deficient cellular control mechanisms that give rise to diverticuli, fistulas, and cancers (9, 41). Repair mechanims are not only involved in healing from Article published online before print. See web site for date of publication ().