Comparative transcriptional analysis between susceptible and resistant populations of Aedes (Stegomyia) aegypti (Linnaeus, 1762) after malathion exposure.

Aedes aegypti is an important vector of arboviruses, including dengue, chikungunya and Zika. The application of synthetic insecticides is a frequently used strategy to control this insect. Malathion is an organophosphate insecticide that was widely used in Brazil in the 1980s and 1990s to control the adult form of A. aegypti. In situations where resistance to currently used insecticides is detected, the use of malathion may be resumed as a control measure. Many studies have confirmed resistance to malathion, however, comparative studies of differential gene expression of the entire transcriptome of resistant and susceptible insects are scarce. Therefore, understanding the molecular basis of resistance to this insecticide in this species is extremely important. In this paper, we present the first transcriptomic description of susceptible and resistant strains of A. aegypti challenged with malathion. Guided transcriptome assembly resulted in 39,904 transcripts, where 2133 differentially expressed transcripts were detected, and three were validated by RT-qPCR. Enrichment analysis for these identified transcripts resulted in 13 significant pathways (padj < 0.05), 8 associated with down-regulated and 5 with up-regulated transcripts in treated resistant insects. It was possible to divide the transcripts according to the mechanism of action into three main groups: (i) genes involved in detoxification metabolic pathways; (ii) genes of proteins located in the membrane/extracellular region; and (iii) genes related to DNA integration/function. These results are important in advancing knowledge of genes related to resistance mechanisms in this insect, enabling the development of effective technologies and strategies for managing insecticide resistance.

Long-read and short-read RNA-seq reveal the transcriptional regulation characteristics of PICK1 in Baoshan pig testis.

PICK1 plays a crucial role in mammalian spermatogenesis. Here, we integrated single-molecule long-read and short-read sequencing to comprehensively examine PICK1 expression patterns in adult Baoshan pig (BS) testes. We identified the most important transcript ENSSSCT00000000120 of PICK1, obtaining its full-length coding sequence (CDS) spanning 1254 bp. Gene structure analysis located PICK1 on pig chromosome 5 with 14 exons. Protein structure analysis reflected that PICK1 consisted of 417 amino acids containing two conserved domains, PDZ and BAR_PICK1. Phylogenetic analysis underscored the evolutionary conservation and homology of PICK1 across different mammalian species. Evaluation of protein interaction network, KEGG, and GO pathways implied that interacted with 50 proteins, predominantly involved in glutamatergic synapses, amphetamine addiction, neuroactive ligand-receptor interactions, dopaminergic synapses, and synaptic vesicle recycling, and PICK1 exhibited significant correlation with DLG4 and TBC1D20. Functional annotation identified that PICK1 was involved in 9 GOs, including seven cellular components and two molecular functions. ceRNA network analysis suggested BS PICK1 was regulated by seven miRNA targets. Moreover, qPCR expression analysis across 15 tissues highlighted that PICK1 was highly expressed in the bulbourethral gland and testis. Subcellular localization analysis in ST (Swine Tesits) cells demonstrated that PICK1 significantly localized within the cytoplasm. Overall, our findings shed new light on PICK1's role in BS reproduction, providing a foundation for further functional studies of PICK1.

Laser-Assisted Microdissection and High-Throughput RNA Sequencing of the Arabidopsis Gynoecium Medial and Lateral Domains.

For obtaining insights into gene networks during plant reproductive development, having transcriptomes of specific cells from developmental stages as starting points is very useful. During development, there is a balance between cell proliferation and differentiation, and many cell and tissue types are formed. While there is a wealth of transcriptome data available, it is mostly at the organ level and not at specific cell or tissue type level. Therefore, methods to isolate specific cell and tissue types are needed. One method is fluorescent activated cell sorting (FACS), but it has limitations such as requiring marker lines and protoplasting. Recently, single-cell/nuclei isolation methods have been developed; however, a minimum amount of genetic information (marker genes) is needed to annotate/predict the resulting cell clusters in these experiments. Another technique that has been known for some time is laser-assisted microdissection (LAM), where specific cells are microdissected and collected using a laser mounted on a microscope platform. This technique has advantages over the others because no fluorescent marker lines must be made, no marker genes must be known, and no protoplasting must be done. The LAM technique consists in tissue fixation, tissue embedding and sectioning using a microtome, microdissection and collection of the cells of interest on the microscope, and finally RNA extraction, library preparation, and RNA sequencing. In this protocol, we implement the use of normal slides instead of the membrane slides commonly used for LAM. We applied this protocol to obtain the transcriptomes of specific tissues during the development of the gynoecium of Arabidopsis. Key features • Laser-assisted microdissection (LAM) allows the isolation of specific cells or tissues. • Normal slides can be used for LAM. • It allows the identification of the transcriptional profiles of specific tissues of the Arabidopsis gynoecium.

Comprehensive analysis of secretome and transcriptome stability of Wharton jelly mesenchymal stromal cells during good manufacturing practice-compliant production.

BACKGROUND: Mesenchymal stromal cells (MSCs) hold promise for cell-based therapies due to their ability to stimulate tissue repair and modulate immune responses. Umbilical cord-derived MSCs from Wharton jelly (WJ) offer advantages such as low immunogenicity and potent immune modulatory effects. However, ensuring consistent quality and safety throughout their manufacturing process remains critical. RNA sequencing (RNA-seq) emerges as a crucial tool for assessing genetic stability and expression dynamics in cell-based therapeutic products. METHODS: We examined the secretome and transcriptome of WJ-MSC signatures throughout Good Manufacturing Practice (GMP) production, focusing on the performance of total RNA or Massive Analysis of cDNA Ends (MACE) sequencing. RESULTS: Through extensive transcriptomic analysis, we demonstrated consistent stability of WJ-MSC expression signatures across different manufacturing stages. Notably, MACE-seq showed improved identification of key expression patterns related to senescence and immunomodulation. CONCLUSIONS: These findings highlight the potential of MACE-seq as a quality assessment tool for WJ-MSC-based therapies, ensuring their efficacy and safety in clinical applications. Importantly, MACE-seq demonstrated its value in characterizing WJ-MSC-derived products, offering insights that traditional assays cannot provide.

Deciphering genetic and nongenetic factors underlying tumour dormancy: insights from multiomics analysis of two syngeneic MRD models of melanoma and leukemia.

BACKGROUND: Tumour dormancy, a resistance mechanism employed by cancer cells, is a significant challenge in cancer treatment, contributing to minimal residual disease (MRD) and potential relapse. Despite its clinical importance, the mechanisms underlying tumour dormancy and MRD remain unclear. In this study, we employed two syngeneic murine models of myeloid leukemia and melanoma to investigate the genetic, epigenetic, transcriptomic and protein signatures associated with tumour dormancy. We used a multiomics approach to elucidate the molecular mechanisms driving MRD and identify potential therapeutic targets. RESULTS: We conducted an in-depth omics analysis encompassing whole-exome sequencing (WES), copy number variation (CNV) analysis, chromatin immunoprecipitation followed by sequencing (ChIP-seq), transcriptome and proteome investigations. WES analysis revealed a modest overlap of gene mutations between melanoma and leukemia dormancy models, with a significant number of mutated genes found exclusively in dormant cells. These exclusive genetic signatures suggest selective pressure during MRD, potentially conferring resistance to the microenvironment or therapies. CNV, histone marks and transcriptomic gene expression signatures combined with Gene Ontology (GO) enrichment analysis highlighted the potential functional roles of the mutated genes, providing insights into the pathways associated with MRD. In addition, we compared "murine MRD genes" profiles to the corresponding human disease through public datasets and highlighted common features according to disease progression. Proteomic analysis combined with multi-omics genetic investigations, revealed a dysregulated proteins signature in dormant cells with minimal genetic mechanism involvement. Pathway enrichment analysis revealed the metabolic, differentiation and cytoskeletal remodeling processes involved in MRD. Finally, we identified 11 common proteins differentially expressed in dormant cells from both pathologies. CONCLUSIONS: Our study underscores the complexity of tumour dormancy, implicating both genetic and nongenetic factors. By comparing genomic, transcriptomic, proteomic, and epigenomic datasets, our study provides a comprehensive understanding of the molecular landscape of minimal residual disease. These results provide a robust foundation for forthcoming investigations and offer potential avenues for the advancement of targeted MRD therapies in leukemia and melanoma patients, emphasizing the importance of considering both genetic and nongenetic factors in treatment strategies.

Fruit sugar hub: gene regulatory network associated with soluble solids content (SSC) in Prunus persica.

Chilean peach growers have achieved worldwide recognition for their high-quality fruit products. Among the main factors influencing peach fruit quality, sweetness is pivotal for maintaining the market's competitiveness. Numerous studies have been conducted in different peach-segregating populations to unravel SSC regulation. However, different cultivars may also have distinct genetic conformation, and other factors, such as environmental conditions, can significantly impact SSC. Using a transcriptomic approach with a gene co-expression network analysis, we aimed to identify the regulatory mechanism that controls the sugar accumulation process in an 'O × N' peach population. This population was previously studied through genomic analysis, associating LG5 with the genetic control of the SSC trait. The results obtained in this study allowed us to identify 91 differentially expressed genes located on chromosome 5 of the peach genome as putative new regulators of sugar accumulation in peach, together with a regulatory network that involves genes directly associated with sugar transport (PpSWEET15), cellulose biosynthesis (PpCSLG2), flavonoid biosynthesis (PpPAL1), pectin modifications (PpPG, PpPL and PpPMEi), expansins (PpEXPA1 and PpEXPA8) and several transcription factors (PpC3H67, PpHB7, PpRVE1 and PpCBF4) involved with the SSC phenotype. These results contribute to a better understanding of the genetic control of the SSC trait for future breeding programs in peaches.

Knowledge-slanted random forest method for high-dimensional data and small sample size with a feature selection application for gene expression data.

The use of prior knowledge in the machine learning framework has been considered a potential tool to handle the curse of dimensionality in genetic and genomics data. Although random forest (RF) represents a flexible non-parametric approach with several advantages, it can provide poor accuracy in high-dimensional settings, mainly in scenarios with small sample sizes. We propose a knowledge-slanted RF that integrates biological networks as prior knowledge into the model to improve its performance and explainability, exemplifying its use for selecting and identifying relevant genes. knowledge-slanted RF is a combination of two stages. First, prior knowledge represented by graphs is translated by running a random walk with restart algorithm to determine the relevance of each gene based on its connection and localization on a protein-protein interaction network. Then, each relevance is used to modify the selection probability to draw a gene as a candidate split-feature in the conventional RF. Experiments in simulated datasets with very small sample sizes ( n ≤ 30 ) comparing knowledge-slanted RF against conventional RF and logistic lasso regression, suggest an improved precision in outcome prediction compared to the other methods. The knowledge-slanted RF was completed with the introduction of a modified version of the Boruta feature selection algorithm. Finally, knowledge-slanted RF identified more relevant biological genes, offering a higher level of explainability for users than conventional RF. These findings were corroborated in one real case to identify relevant genes to calcific aortic valve stenosis.

Exploring Aquaporin Diversity in Elateroidea: Insights From RNA-Seq Data Sets.

Osmoregulation, the physiological regulation of water and ion balance, is vital for the survival of both aquatic and terrestrial insects. In freshwater aquatic insects, such as those within the Lampyridae family, this function is important due to the natural variation of aquatic habitats. Aquaporins play a key role in this process by facilitating the rapid transport of water molecules across cell membranes, maintaining cellular water balance, and adapting to changes in external salinity. In this study, I investigate the genetic diversity and expression levels of aquaporins in Elateroidea, particularly focusing on the Lampyridae family, using transcriptomic data and in silico analyses. The results reveal the diversity of aquaporins and compare gene expression patterns between freshwater aquatic Lampyridae and terrestrial Elateroidea species, such as Lycidae, Phengodidae, and Elateridae. Phylogenetic analyses identify seven distinct clades of aquaporins and uncovered gene duplication events related to the diversification of Elateridae and Lampyridae. A comparative abundance analysis indicated higher aquaporin expression in aquatic fireflies, aligning with the need for efficient osmoregulation in aquatic environments. Additionally, stage-specific expression patterns in Aspisoma lineatum (Neotropical firefly) and Aquatica lateralis (Paleartic firefly) suggest species-specific strategies for coping with osmotic challenges during development. This study provides insights into the evolutionary adaptations of aquaporins in Elateroidea, highlighting their importance in both aquatic and terrestrial insect physiology.

Effects of Arborvitae (Thuja plicata) Essential Oil on Cervical Cancer Cells: Insights into Molecular Mechanisms.

AIMS: This study aimed to assess the effects of AEO in an in vitro model of cell lines derived from cervical cancer-namely, HeLa and SiHa-by screening for AEO's cytotoxic properties and examining its influence on the modulation of gene expression. BACKGROUND: Cervical cancer stands as a prevalent global health concern, affecting millions of women worldwide. The current treatment modalities encompass surgery, radiation, and chemotherapy, but significant limitations and adverse effects constrain their effectiveness. Therefore, exploring novel treatments that offer enhanced efficacy and reduced side effects is imperative. Arborvitae essential oil, extracted from Thuja Plicata, has garnered attention for its antimicrobial, anti-inflammatory, immunomodulatory, and tissue-remodeling properties; however, its potential in treating cervical cancer remains uncharted. OBJECTIVE: The objective of this study was to delve into the molecular mechanisms induced by arborvitae essential oil in order to learn about its anticancer effects on cervical cancer cell lines. METHODS: The methods used in this study were assessments of cell viability using WST-1 and annexin V- propidium iodide, mRNA sequencing, and subsequent bioinformatics analysis. RESULTS: The findings unveiled a dose-dependent cytotoxic effect of arborvitae essential oil on both HeLa and SiHa cell lines. Minor effects were observed only at very low doses in the HaCaT non-tumorigenic human keratinocyte cells. RNA-Seq bioinformatics analysis revealed the regulatory impact of arborvitae essential oil on genes enriched in the following pathways: proteasome, adherens junctions, nucleocytoplasmic transport, cell cycle, proteoglycans in cancer, protein processing in the endoplasmic reticulum, ribosome, spliceosome, mitophagy, cellular senescence, and viral carcinogenesis, among others, in both cell lines. It is worth noting that the ribosome and spliceosome KEGG pathways are the most significantly enriched pathways in HeLa and SiHa cells. CONCLUSION: Arborvitae essential oil shows potential as a cytotoxic and antiproliferative agent against cervical cancer cells, exerting its cytotoxic properties by regulating many KEGG pathways.

Transcriptomic and Gene Expression Analysis of Chemosensory Genes from White Grubs of Hylamorpha elegans (Coleoptera: Scarabaeidae), a Subterranean Pest in South America.

Olfaction and gustation processes play key roles in the life cycle of insects, such as finding and accepting food sources, oviposition sites, and mates, among other fundamental aspects of insect development. In this context, chemosensory genes found in sensory organs (e.g., antennae and maxillary palps) are crucial for understanding insect behaviour, particularly the phytophagous behaviour of insect pests that attack economically important crops. An example is the scarab beetle Hylamorpha elegans, which feeds on the roots of several crops important for livestock in its larval stage. In this study, chemosensory gene candidates of H. elegans white grubs identified through the head transcriptome and phylogenetic and tissue-biased gene expression (antennae, head without antennae, and legs) have been reported. Overall, 47 chemosensory genes were identified (2 ORs, 1 GR, 11 IRs, 9 CSPs, and 24 OBPs). Gene expression analysis revealed the predominant presence of IRs in the legs, whereas ORs and the GR were present in the heads and/or antennae. Particularly, HeleOBP9 and HeleCSP2 were significantly expressed in the head but not in the antennae or legs; these and other genes are discussed as potential targets in the context of H. elegans management.

CCKR signaling map, G-Protein bindings, hormonal regulation, and neural mechanisms may influence the osteogenic/cementogenic differentiation potential of hPDLSCs.

OBJECTIVE: Periodontal regeneration poses challenges due to the periodontium's complexity, relying on mesenchymal cells from the periodontal ligament (hPDLSCs) to regenerate hard tissues like bone and cementum. While some hPDLSCs have high regeneration potential (HOP-hPDLSCs), most are low potential (LOP-hPDLSCs). This study analyzed hPDLSCs from a single donor to minimize inter-individual variability and focus on key differences in differentiation potentials. DESIGN: This study used RNA-seq, genomic databases, and bioinformatics tools to explore signaling pathways (SPs), biological processes (BPs), and molecular functions (MFs) guiding HOP cells to mineralized matrix production. It also investigated limitations of LOP cells and strategies for enhancing their osteo/cementogenesis. RESULTS: In basal conditions, HOP exhibited a multifunctional gene network with higher expression of genes related to osteo/cementogenesis, cell differentiation, immune modulation, stress response, and hormonal regulation. In contrast, LOP focused on steroid hormone biosynthesis and nucleic acid maintenance. During osteo/cementogenic induction, HOP showed strong modulation of genes related to angiogenesis, cell division, mesenchymal differentiation, and extracellular matrix production. LOP demonstrated neural synaptic-related processes and preserved cellular cytoskeleton integrity. CCKR map signaling and G-protein receptor bindings gained significance during osteo/cementogenesis in HOP-hPDLSCs. Both HOP and LOP shared common BPs related to gastrointestinal and reproductive system development. CONCLUSION: The osteo/cementogenic differentiation of HOP cells may be regulated by CCKR signaling, G-protein bindings, and specific hormonal regulation. LOP cells seem committed to neural mechanisms. This study sheds light on hPDLSCs' complex characteristics, offering a deeper understanding of their differentiation potential for future periodontal regeneration research and therapies.

RNAseq analysis of whole zebrafish (Danio rerio) larvae revealed the main cellular biological effects of geosmin and microcystin exposure at environmentally relevant concentrations.

Cyanobacterial blooms are common events that releases secondary metabolites into water posing considerable threats to the environment, wildlife, and public health. Some of these metabolites, such as microcystin, have been extensively studied and associated with harmful effects in mammals and aquatic organisms, while the biological effects of others, like geosmin, remain much less investigated. Enhancing our understanding of cyanotoxins effects on organisms is especially relevant facing the complex scenarios projected due to global warming. The aim of this study was to assess the transcriptional modulation in whole zebrafish (Danio rerio) larvae (n = 9) in response to a 7-days immersion exposure to 3 µg L-1 MCLR or 5 µg L-1 geosmin. No mortality or differences in length gain were observed in zebrafish larvae exposed to environmentally realistic doses of both cyanotoxins. The exposure to MCLR and to geosmin caused the differential expression of 164 and 172 genes respectively, being 23 upregulated by MCLR and 98 upregulated by geosmin. Among the upregulated genes, 16 were shared, while 42 were shared among the downregulated genes. Over-representation analysis identified three enriched GO terms only among the genes upregulated by geosmin: organic hydroxy compound metabolic process (1901615), small molecule biosynthetic process (0044283), and lipid metabolic process (0006629). In fact, the expression of 12 of the 13 genes directly involved in the synthesis of cholesterol from acetyl-CoA was upregulated by geosmin. A chronic upregulation of cholesterol biosynthetic pathway is linked to several diseases and metabolic disorders, including alterations in sex-related hormones. Moreover, our results indicate that geosmin and MCLR acts through different mechanisms. Geosmin does not appear to provoke short-term adverse effects as MCLR but could disrupt the endocrine system by altering the lipid and steroid metabolism.

Single-cell transcriptomic sequencing analysis of mechanistic insights into the IFN-γ signaling pathway in different tumor cells.

PURPOSE: This study aimed to investigate the relationship between the interferon-gamma (IFN-γ) pathway in different tumor microenvironments (TME) and patients' prognosis, as well as the regulatory mechanisms of this pathway in tumor cells. METHODS: Using RNA-seq data from the TCGA database, we analyzed the predictive value of the IFN-γ pathway across various tumors. We employed a univariate Cox regression model to assess the prognostic significance of IFN-γ signaling in different tumor types. Additionally, we analyzed single-cell RNA sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) database to examine the distribution characteristics of the IFN-γ pathway and explore its regulatory mechanisms, highlighting how IFN-γ influenced cellular interactions within the TME. RESULTS: Our analysis revealed a significant association between the IFN-γ pathway and adverse prognosis in pan-cancer tissues (P < 0.001). Interestingly, this correlation varied regarding positive and negative regulation across different tumor types. Through a detailed examination of scRNA-seq data, we found that the IFN-γ pathway exerted substantial regulatory effects on stromal and immune cells. In contrast, its expression and regulatory patterns in tumor cells exhibited diversity and heterogeneity. Further analysis indicated that the IFN-γ pathway not only enhanced the immunogenicity of tumor cells but also inhibited their proliferation. Cell-cell interaction analysis confirmed the pivotal role of the IFN-γ pathway within the overall regulatory network. Moreover, we identified HMGB2 (high mobility group box 2) in T cells as a potential key regulator of tumor cell proliferation. CONCLUSIONS: The IFN-γ pathway exhibited a dual function by both suppressing tumor cell proliferation and enhancing their immunogenicity, positioning it as a pivotal target for refined cancer diagnosis and cancer strategies.

Response of wild aquatic insect communities to thermal variation through comparative landscape transcriptomics.

Fluctuations in temperature are recognized as a potent driver of selection pressure, fostering genomic variations that are crucial for the adaptation and survival of organisms under selection. Notably, water temperature is a pivotal factor influencing aquatic organism persistence. By comprehending how aquatic organisms respond to shifts in water temperature, we can understand their potential physiological adaptations to environmental change in one or multiple species. This, in turn, contributes to the formulation of biologically relevant guidelines for the landscape scale transcriptome profile of organisms in lotic systems. Here, we investigated the distinct responses of seven stream stonefly species, collected from four geographical regions across Japan, to variations in temperature, including atmospheric and water temperatures. We achieved this by assessing the differences in gene expression through RNA-sequencing within individual species and exploring the patterns of community-genes among different species. We identified 735 genes that exhibited differential expressions across the temperature gradient. Remarkably, the community displayed expression levels differences of respiration and metabolic genes. Additionally, the diversity in molecular functions appeared to be linked to spatial variation, with water temperature differences potentially contributing to the overall functional diversity of genes. We found 22 community-genes with consistent expression patterns among species in response to water temperature variations. These genes related to respiration, metabolism and development exhibited a clear gradient providing robust evidence of divergent adaptive responses to water temperature. Our findings underscore the differential adaptation of stonefly species to local environmental conditions, suggesting that shared responses in gene expression may occur across multiple species under similar environmental conditions. This study emphasizes the significance of considering various species when assessing the impacts of environmental changes on aquatic insect communities and understanding potential mechanisms to cope with such changes.

Novel Candidate Genes Involved in an Initial Stage of White Striping Development in Broiler Chickens.

White striping (WS) is a myopathy characterized by the appearance of white stripes parallel to the muscle fibers in the breast of broiler chickens, composed of adipose and connective tissues. This condition causes economic losses and, although common, its etiology remains poorly understood. Hence, the objective was to identify genes and biological mechanisms involved in the early stages of WS using a paternal broiler line that grows slightly slower than commercial ones, at 35 days of age, through the RNA sequencing of the pectoralis major muscle. Thirty genes were differentially expressed between normal and WS-affected chickens, with 23 upregulated and 7 downregulated in the affected broilers. Of these, 14 genes are novel candidates for WS and are implicated in biological processes related to muscle development (CEPBD, DUSP8, METTL21EP, NELL2, and UBE3D), lipid metabolism (PDK4, DDIT4, FKBP5, DGAT2, LIPG, TDH, and RGCC), and collagen (COL4A5 and COL4A6). Genes related to changes in muscle fiber type and the processes of apoptosis, autophagy, proliferation, and differentiation are possibly involved with the initial stage of WS development. In contrast, the genes linked to lipid metabolism and collagen may have their expression altered due to the progression of the myopathy.

Integrative Analysis of Transcriptomic Profiles and Physiological Responses Provide New Insights into Drought Stress Tolerance in Oil Palm (Elaeis guineensis Jacq.).

Oil palm (Elaeis guineensis Jacq.) is a highly productive crop economically significant for food, cosmetics, and biofuels. Abiotic stresses such as low water availability, salt accumulation, and high temperatures severely impact oil palm growth, physiology, and yield by restricting water flux among soil, plants, and the environment. While drought stress's physiological and biochemical effects on oil palm have been extensively studied, the molecular mechanisms underlying drought stress tolerance remain unclear. Under water deficit conditions, this study investigates two commercial E. guineensis cultivars, IRHO 7001 and IRHO 2501. Water deficit adversely affected the physiology of both cultivars, with IRHO 2501 being more severely impacted. After several days of water deficit, there was a 40% reduction in photosynthetic rate (A) for IRHO 7001 and a 58% decrease in IRHO 2501. Further into the drought conditions, there was a 75% reduction in A for IRHO 7001 and a 91% drop in IRHO 2501. Both cultivars reacted to the drought stress conditions by closing stomata and reducing the transpiration rate. Despite these differences, no significant variations were observed between the cultivars in stomatal conductance, transpiration, or instantaneous leaf-level water use efficiency. This indicates that IRHO 7001 is more tolerant to drought stress than IRHO 2501. A differential gene expression and network analysis was conducted to elucidate the differential responses of the cultivars. The DESeq2 algorithm identified 502 differentially expressed genes (DEGs). The gene coexpression network for IRHO 7001 comprised 274 DEGs and 46 predicted HUB genes, whereas IRHO 2501's network included 249 DEGs and 3 HUB genes. RT-qPCR validation of 15 DEGs confirmed the RNA-Seq data. The transcriptomic profiles and gene coexpression network analysis revealed a set of DEGs and HUB genes associated with regulatory and transcriptional functions. Notably, the zinc finger protein ZAT11 and linoleate 13S-lipoxygenase 2-1 (LOX2.1) were overexpressed in IRHO 2501 but under-expressed in IRHO 7001. Additionally, phytohormone crosstalk was identified as a central component in the response and adaptation of oil palm to drought stress.

Identification of Novel Bacterial Microproteins Encoded by Small Open Reading Frames Using a Computational Proteogenomics Workflow.

Genome annotation has historically ignored small open reading frames (smORFs), which encode a class of proteins shorter than 100 amino acids, collectively referred to as microproteins. This cutoff was established to avoid thousands of false positives due to limitations of pure genomics pipelines. Proteogenomics, a computational approach that combines genomics, transcriptomics, and proteomics, makes it possible to accurately identify these short sequences by overlaying different levels of omics evidence. In this chapter, we showcase the use of µProteInS, a bioinformatics pipeline developed for the identification of unannotated microproteins encoded by smORFs in bacteria. The workflow covers all the steps from quality control and transcriptome assembly to the scoring and post-processing of mass spectrometry data. Additionally, we provide an example on how to apply the pipeline's machine learning method to identify high-confidence spectra and pinpoint the most reliable identifications from large datasets.

How does the age of control individuals hinder the identification of target genes for Huntington's disease?

Several studies have compared the transcriptome across various brain regions in Huntington's disease (HD) gene-positive and neurologically normal individuals to identify potential differentially expressed genes (DEGs) that could be pharmaceutical or prognostic targets for HD. Despite adhering to technical recommendations for optimal RNA-Seq analysis, none of the genes identified as upregulated in these studies have yet demonstrated success as prognostic or therapeutic targets for HD. Earlier studies included samples from neurologically normal individuals older than the HD gene-positive group. Considering the gradual transcriptional changes induced by aging in the brain, we posited that utilizing samples from older controls could result in the misidentification of DEGs. To validate our hypothesis, we reanalyzed 146 samples from this study, accessible on the SRA database, and employed Propensity Score Matching (PSM) to create a "virtual" control group with a statistically comparable age distribution to the HD gene-positive group. Our study underscores the adverse impact of using neurologically normal individuals over 75 as controls in gene differential expression analysis, resulting in false positives and negatives. We conclusively demonstrate that using such old controls leads to the misidentification of DEGs, detrimentally affecting the discovery of potential pharmaceutical and prognostic markers. This underscores the pivotal role of considering the age of control samples in RNA-Seq analysis and emphasizes its inclusion in evaluating best practices for such investigations. Although our primary focus is HD, our findings suggest that judiciously selecting age-appropriate control samples can significantly improve best practices in differential expression analysis.

Fine-Tuning of Arabidopsis thaliana Response to Endophytic Colonization by Gluconacetobacter diazotrophicus PAL5 Revealed by Transcriptomic Analysis.

Gluconacetobacter diazotrophicus is a diazotrophic endophytic bacterium that promotes the growth and development of several plant species. However, the molecular mechanisms activated during plant response to this bacterium remain unclear. Here, we used the RNA-seq approach to understand better the effect of G. diazotrophicus PAL5 on the transcriptome of shoot and root tissues of Arabidopsis thaliana. G. diazotrophicus colonized A. thaliana roots and promoted growth, increasing leaf area and biomass. The transcriptomic analysis revealed several differentially expressed genes (DEGs) between inoculated and non-inoculated plants in the shoot and root tissues. A higher number of DEGs were up-regulated in roots compared to shoots. Genes up-regulated in both shoot and root tissues were associated with nitrogen metabolism, production of glucosinolates and flavonoids, receptor kinases, and transcription factors. In contrast, the main groups of down-regulated genes were associated with pathogenesis-related proteins and heat-shock proteins in both shoot and root tissues. Genes encoding enzymes involved in cell wall biogenesis and modification were down-regulated in shoots and up-regulated in roots. In contrast, genes associated with ROS detoxification were up-regulated in shoots and down-regulated in roots. These results highlight the fine-tuning of the transcriptional regulation of A. thaliana in response to colonization by G. diazotrophicus PAL5.

Diffusion on PCA-UMAP Manifold: The Impact of Data Structure Preservation to Denoise High-Dimensional Single-Cell RNA Sequencing Data.

Single-cell transcriptomics (scRNA-seq) is revolutionizing biological research, yet it faces challenges such as inefficient transcript capture and noise. To address these challenges, methods like neighbor averaging or graph diffusion are used. These methods often rely on k-nearest neighbor graphs from low-dimensional manifolds. However, scRNA-seq data suffer from the 'curse of dimensionality', leading to the over-smoothing of data when using imputation methods. To overcome this, sc-PHENIX employs a PCA-UMAP diffusion method, which enhances the preservation of data structures and allows for a refined use of PCA dimensions and diffusion parameters (e.g., k-nearest neighbors, exponentiation of the Markov matrix) to minimize noise introduction. This approach enables a more accurate construction of the exponentiated Markov matrix (cell neighborhood graph), surpassing methods like MAGIC. sc-PHENIX significantly mitigates over-smoothing, as validated through various scRNA-seq datasets, demonstrating improved cell phenotype representation. Applied to a multicellular tumor spheroid dataset, sc-PHENIX identified known extreme phenotype states, showcasing its effectiveness. sc-PHENIX is open-source and available for use and modification.