Comparison Of Gene Expression Levels Research Articles

Extensive transcriptome data providing great efficacy in genetic research and adaptive gene discovery: a case study of Elymus sibiricus L. (Poaceae, Triticeae).

Genetic markers play a central role in understanding genetic diversity, speciation, evolutionary processes, and how species respond to environmental stresses. However, conventional molecular markers are less effective when studying polyploid species with large genomes. In this study, we compared gene expression levels in 101 accessions of Elymus sibiricus, a widely distributed allotetraploid forage species across the Eurasian continent. A total of 20,273 high quality transcriptomic SNPs were identified. In addition, 72,344 evolutionary information loci of these accessions of E. sibiricus were identified using genome skimming data in conjunction with the assembled composite genome. The population structure results suggest that transcriptome SNPs were more effective than SNPs derived from genome skimming data in revealing the population structure of E. sibiricus from different locations, and also outperformed gene expression levels. Compared with transcriptome SNPs, the investigation of population-specifically-expressed genes (PSEGs) using expression levels revealed a larger number of locally adapted genes mainly involved in the ion response process in the Sichuan, Inner Mongolia, and Xizang geographical groups. Furthermore, we performed the weighted gene co-expression network analysis (WGCNA) and successfully identified potential regulators of PSEGs. Therefore, for species lacking genomic information, the use of transcriptome SNPs is an efficient approach to perform population structure analysis. In addition, analyzing genes under selection through nucleotide diversity and genetic differentiation index analysis based on transcriptome SNPs, and exploring PSEG through expression levels is an effective method for analyzing locally adaptive genes.

Advances in Inflammatory Bowel Disease Diagnostics: Machine Learning and Genomic Profiling Reveal Key Biomarkers for Early Detection.

This study, utilizing high-throughput technologies and Machine Learning (ML), has identified gene biomarkers and molecular signatures in Inflammatory Bowel Disease (IBD). We could identify significant upregulated or downregulated genes in IBD patients by comparing gene expression levels in colonic specimens from 172 IBD patients and 22 healthy individuals using the GSE75214 microarray dataset. Our ML techniques and feature selection methods revealed six Differentially Expressed Gene (DEG) biomarkers (VWF, IL1RL1, DENND2B, MMP14, NAAA, and PANK1) with strong diagnostic potential for IBD. The Random Forest (RF) model demonstrated exceptional performance, with accuracy, F1-score, and AUC values exceeding 0.98. Our findings were rigorously validated with independent datasets (GSE36807 and GSE10616), further bolstering their credibility and showing favorable performance metrics (accuracy: 0.841, F1-score: 0.734, AUC: 0.887). Our functional annotation and pathway enrichment analysis provided insights into crucial pathways associated with these dysregulated genes. DENND2B and PANK1 were identified as novel IBD biomarkers, advancing our understanding of the disease. The validation in independent cohorts enhances the reliability of these findings and underscores their potential for early detection and personalized treatment of IBD. Further exploration of these genes is necessary to fully comprehend their roles in IBD pathogenesis and develop improved diagnostic tools and therapies. This study significantly contributes to IBD research with valuable insights, potentially greatly enhancing patient care.

Isolation, characterization, and application of bacteriophage on Vibrio parahaemolyticus biofilm to control seafood contamination

ObjectiveThis study intended to isolate a Vibrio-particular phage from the natural environment, analyse its characteristics and genome sequence, and investigate its reduction effect on V. parahaemolyticus biofilm as a biocontrol agent in squid and mackerel. MethodsAmong 21 phages, phage CAU_VPP01, isolated from beach mud, was chosen for further experiments based on host range and EOP tests. When examining the reduction effect of phage CAU_VPP01 against Vibrio parahaemolyticus biofilms on surfaces (stainless steel [SS] and polyethylene terephthalate [PET]) and food surfaces (squid and mackerel). ResultsThe phage showed the most excellent reduction effect at a multiplicity-of-infection (MOI) 10. Three-dimensional images acquired with confocal laser scanning microscopy (CLSM) analysis were quantified using COMSTAT, which showed that biomass, average thickness, and roughness coefficient decreased when treated with the phage. Colour and texture analysis confirmed that the quality of squid and mackerel was maintained after the phage treatment. Finally, a comparison of gene expression levels determined by qRT-PCR analysis showed that the phage treatment induced a decrease in the gene expression of flaA, vp0962, andluxS, as examples. ConclusionThis study indicated that Vibrio-specific phage CAU_VPP01 effectively controlled V. parahaemolyticus biofilms under various conditions and confirmed that the isolated phage could possibly be used as an effective biocontrol weapon in the seafood manufacturing industry.

Serine proteinase inhibitors from Nicotiana benthamiana, a nonpreferred host plant, inhibit the growth of Myzus persicae (green peach aphid).

The green peach aphid (Myzus persicae) is a severe agricultural crop pest that has developed resistance to most current control methods, requiring the urgent development of novel strategies. Plant proteinase inhibitors (PINs) are small proteins that protect plants against pathogens and/or herbivores, likely by preventing efficient protein digestion. We identified 67 protease genes in the transcriptomes of three M. persicae lineages (USDA-Red, G002 and G006). Comparison of gene expression levels in aphid guts and whole aphids showed that several proteases, including a highly expressed serine protease, are significantly overexpressed in the guts. Furthermore, we identified three genes encoding serine protease inhibitors (SerPIN-II1, 2 and 3) in Nicotiana benthamiana, which is a nonpreferred host for M. persicae. Using virus-induced gene silencing (VIGS) with a tobacco rattle virus (TRV) vector and overexpression with a turnip mosaic virus (TuMV) vector, we demonstrated that N. benthamiana SerPIN-II1 and SerPIN-II2 cause reduced survival and growth, but do not affect aphid protein content. Likewise, SerPIN-II3 overexpression reduced survival and growth, and serpin-II3 knockout mutations, which we generated using CRISPR/Cas9, increased survival and growth. Protein content was significantly increased in aphids fed on SerPIN-II3 overexpressing plants, yet it was decreased in aphids fed on serpin-II3 mutants. Our results show that three PIN-IIs from N. benthamiana, a nonpreferred host plant, effectively inhibit M. persicae survival and growth, thereby representing a new resource for the development of aphid-resistant crop plants. © 2024 Society of Chemical Industry.

Immune-Related Gene Profiles and Differential Expression in the Grey Garden Slug Deroceras reticulatum Infected with the Parasitic Nematode Phasmarhabditis hermaphrodita.

The grey garden slug (Deroceras reticulatum), a common terrestrial slug native to Europe with a global distribution including North America, is commonly considered the most severe slug pest in agriculture. The nematode Phasmarhabditis hermaphrodita, which has been used in the U.K. and Europe as a commercial biocontrol agent since 1994, has also recently been collected in Oregon and California and has long been considered a candidate biocontrol agent for slug management in the U.S. In this study, we report differential gene expressions in nematode-infected slugs using RNA-seq to identify slug immune-related genes against nematodes. Comparison of gene expression levels between the whole bodies of a nematode-infected slug (N-S) and an uninfected control slug (C-S) revealed that there were a total of 39,380 regulated unigenes, of which 3084 (3%) were upregulated and 6761 (6%) were downregulated at greater than 2-fold change (FC > 2) in the nematode-infected slug. To further investigate the biological functions of differentially expressed genes (DEGs), gene ontology (GO) and functional enrichment analysis were performed to map the DEGs to terms in the GO, eukaryotic ortholog groups of proteins (KOG) and Kyoto Encyclopedia of Genes and Genome Pathway (KEGG) databases. Among these DEGs, approximately 228 genes associated with immunity or immune-related pathways were upregulated 2-fold or more in the N-S compared to C-S. These genes include toll, Imd, JNK, scavenger receptors (SCRs), C-type lectins (CTLs), immunoglobulin-like domains, and JAK/STAT63 signaling pathways. From the RNA-seq results, we selected 18 genes and confirmed their expression levels by qRT-PCR. Our findings provide insights into the immune response of slugs during nematode infection. These studies provide fundamental information that will be valuable for the development of new methods of pest slug control using pathogenic nematodes in the field.

Abstract 5826: Comprehensive analysis with single-cell RNA sequence and spatial transcriptomics unravels distinctive expression profile of apoptotic-related genes in EGFR-mutated lung cancer

Abstract Despite an initial marked response to targeted therapy with tyrosine kinase inhibitors (TKIs) in EGFR-mutated lung cancer, the duration of response is limited due to the inevitable development of acquired resistance. Anti- and pro-apoptotic genes play an important role in the survival of tumor cells. Currently, variations in these gene expression levels are not well characterized due to the complex interplay between the inducement of expression changes by EGFR-TKIs and the presence of inter- and intra-tumor heterogeneity. Here, a comprehensive analysis of apoptosis-related genes, including BCL-2 family members and the IAP family members, was conducted via single-cell RNA sequence (scRNA-seq) and spatial transcriptomics. scRNA-seq captured changes in apoptosis-related gene expression after EGFR-TKI treatment using different EGFR-mutated lung cancer cell lines. Notably, BCL2L1 expression increased, whereas MCL1 expression decreased after EGFR-TKI treatment. Other anti- and pro-apoptotic genes did not display consistent trends in the cell lines used. Additionally, scRNA-seq was carried out on samples collected from patients with EGFR-mutated lung cancer after the development of resistance to EGFR-TKIs in order to validate the results obtained from cell line data and to compare gene expression levels between tumor and non-tumor cells. BCL2L1 exhibited high expression specifically in tumor cells; in contrast, MCL1 expression was lower in tumor cells compared to non-tumor cells. Moreover, BAD and XIAP were highly expressed in a tumor-specific manner. To further corroborate the scRNA-seq findings and delineate the spatial heterogeneity in tumors, spatial transcriptomics was performed using EGFR-driven lung cancer transgenic mouse specimens in three conditions: prior to treatment, during therapeutic response after short-term treatment, and following acquired resistance to EGFR-TKIs. Spatial transcriptomics data demonstrated that an increased BCL2L1 expression was observed in tumor tissues and that MCL1 expression was significantly higher in tissue adjacent to tumors than in tumors. Finally, we demonstrated that genetic ablation of BCL2L1 and pharmacological inhibition of BCL2L1 overcame or delayed resistance to EGFR-TKIs in vitro and in vivo. Overall, BCL2L1 is particularly important for tumor cell survival during the emergence of drug tolerance and the development of acquired resistance to EGFR-TKIs. Citation Format: Motohiro Izumi, Masanori Fujii, Vivian Ho, Ikei S. Kobayashi, Susumu S. Kobayashi. Comprehensive analysis with single-cell RNA sequence and spatial transcriptomics unravels distinctive expression profile of apoptotic-related genes in EGFR-mutated lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5826.

PCTA, a pan-cancer cell line transcriptome atlas

A substantial volume of RNA sequencing data have been generated from cancer cell lines. However, it requires specific bioinformatics skills to compare gene expression levels across cell lines. This has hindered non-bioinformaticians from fully utilizing these valuable datasets in their research. To bridge this gap, we established a curated Pan-cancer Cell Line Transcriptome Atlas (PCTA) dataset. This resource aims to provide a user-friendly platform, allowing researchers without extensive bioinformatics expertise to access and leverage the wealth of information within the dataset for their studies. The PCTA dataset encompasses the expression matrix of 24,965 genes, featuring data from 84,385 samples derived from 5677 studies. This comprehensive compilation spans 535 cell lines, representing a spectrum of 114 cancer types originating from 30 diverse tissue types. On UMAP plots, cell lines originating from the same type of tissue tend to cluster together, illustrating the dataset's ability to capture biological relationships. Additionally, an interactive and user-friendly web application (https://pcatools.shinyapps.io/PCTA_app/) was developed for researchers to explore the PCTA dataset. This platform allows users to examine the expression of their genes of interest across a diverse array of samples.

Mucosal Genes Encoding Clock, Inflammation and Their Mutual Regulators Are Disrupted in Pediatric Patients with Active Ulcerative Colitis.

Patients with active ulcerative colitis (UC) display a misalignment of the circadian clock, which plays a vital role in various immune functions. Our aim was to characterize the expression of clock and inflammation genes, and their mutual regulatory genes in treatment-naïve pediatric patients with UC. Using the Inflammatory Bowel Disease Transcriptome and Metatranscriptome Meta-Analysis (IBD TaMMA) platform and R algorithms, we analyzed rectal biopsy transcriptomic data from two cohorts (206 patients with UC vs. 20 healthy controls from the GSE-109142 study, and 43 patients with UC vs. 55 healthy controls from the GSE-117993 study). We compared gene expression levels and correlation of clock genes (BMAL1, CLOCK, PER1, PER2, CRY1, CRY2), inflammatory genes (IκB, IL10, NFκB1, NFκB2, IL6, TNFα) and their mutual regulatory genes (RORα, RORγ, REV-ERBα, PGC1α, PPARα, PPARγ, AMPK, SIRT1) in patients with active UC and healthy controls. The clock genes BMAL1, CLOCK, PER1 and CRY1 and the inflammatory genes IκB, IL10, NFκB1, NFκB2, IL6 and TNFα were significantly upregulated in patients with active UC. The genes encoding the mutual regulators RORα, RORγ, PGC1α, PPARα and PPARγ were significantly downregulated in patients with UC. A uniform pattern of gene expression was found in healthy controls compared to the highly variable expression pattern in patients with UC. Among the healthy controls, inflammatory genes were positively correlated with clock genes and they all showed reduced expression. The difference in gene expression levels was associated with disease severity and endoscopic score but not with histological score. In patients with active UC, clock gene disruption is associated with abnormal mucosal immune response. Disrupted expression of genes encoding clock, inflammation and their mutual regulators together may play a role in active UC.

Transcriptomic comparison between populations selected for higher and lower mobility in the red flour beetle Tribolium castaneum

Movement is an important behavior observed in a wide range of taxa. Previous studies have examined genes controlling movement using wing polymorphic insects and genes controlling wing size. However, few studies have investigated genes controlling movement activity rather than morphological traits. In the present study, we conducted RNA sequencing using populations with higher (WL) and lower (WS) mobility established by artificial selection in the red flour beetle Tribolium castaneum and compared gene expression levels between selected populations with two replicate lines. As a result, we found significant differences between the selected populations in 677 genes expressed in one replicate line and 1198 genes expressed in another replicate line, of which 311 genes were common to the two replicate lines. Furthermore, quantitative PCR focusing on 6 of these genes revealed that neuropeptide F receptor gene (NpF) was significantly more highly expressed in the WL population than in the WS population, which was common to the two replicate lines. We discuss differences in genes controlling movement between walking activity and wing polymorphism.

An RNA-Seq Data Analysis Pipeline.

In this chapter, we present an established pipeline for analyzing RNA-Seq data, which involves a step-by-step flow starting from raw data obtained from a sequencer and culminating in the identification of differentially expressed genes with their functional characterization. The pipeline is divided into three sections, each addressing crucial stages of the analysis process. The first section covers the initial steps of the pipeline, including downloading of the data of interest and performing quality control assessment. Assessment ensures that the data used for analysis is reliable and suitable for downstream analyses. In the second section, gene-level quantification is performed, which entails quantification of expression levels of genes in the samples. The third and final section is focused on differential expression analysis, which involves comparing gene expression levels between two or more conditions. This step helps identify genes that show significant differences in expression levels under different experimental conditions. To facilitate accessibility and reproducibility, we have provided an online repository containing all scripts and files. Additionally, custom scripts are available, enabling users to modify the pipeline's output for various downstream analyses. By following this pipeline, researchers can effectively analyze RNA-Seq data and gain valuable insights into gene expression patterns and, furthermore, the understanding of biological processes.

Biocontrol of Peach Gummosis by Bacillus velezensis KTA01 and Its Antifungal Mechanism.

Peach tree gummosis is a botanical anomaly distinguished by the secretion of dark-brown gum from the shoots of peach trees, and Botryosphaeria dothidea has been identified as one of the fungal species responsible for its occurrence. In South Korea, approximately 80% of gummosis cases are linked to infections caused by B. dothidea. In this study, we isolated microbes from the soil surrounding peach trees exhibiting antifungal activity against B. dothidea. Subsequently, we identified several bacterial strains as potential candidates for a biocontrol agent. Among them, Bacillus velezensis KTA01 displayed the most robust antifungal activity and was therefore selected for further analysis. To investigate the antifungal mechanism of B. velezensis KTA01, we performed tests to assess cell wall degradation and siderophore production. Additionally, we conducted reverse transcription-quantitative polymerase chain reaction (RT-qPCR) analysis based on whole-genome sequencing to confirm the presence of genes responsible for the biosynthesis of lipopeptide compounds, a well-known characteristic of Bacillus spp., and to compare gene expression levels. Moreover, we extracted lipopeptide compounds using methanol and subjected them to both antifungal activity testing and high-performance liquid chromatography (HPLC) analysis. The experimental findings presented in this study unequivocally demonstrate the promising potential of B. velezensis KTA01 as a biocontrol agent against B. dothidea KACC45481, the pathogen responsible for causing peach tree gummosis.

Evaluating the stability of host-reference gene expression and simultaneously quantifying parasite burden and host immune responses in murine malaria

The efficacy of pre-erythrocytic stage malaria antigens or vaccine platforms is routinely assessed in murine models challenged with Plasmodium sporozoites. Relative liver-stage parasite burden is quantified using reverse transcription quantitative PCR (RTqPCR), which relies on constitutively expressed endogenous control reference genes. However, the stability of host-reference gene expression for RTqPCR analysis following Plasmodium challenge and immunization has not been systematically evaluated. Herein, we evaluated the stability of expression of twelve common RTqPCR reference genes in a murine model of Plasmodium yoelii sporozoite challenge and DNA-adenovirus IV 'Prime-Target' immunization. Significant changes in expression for six of twelve reference genes were shown by one-way ANOVA, when comparing gene expression levels among challenge, immunized, and naïve mice groups. These changes were attributed to parasite challenge or immunization when comparing group means using post-hoc Bonferroni corrected multiple comparison testing. Succinate dehydrogenase (SDHA) and TATA-binding protein (TBP) were identified as stable host-reference genes suitable for relative RTqPCR data normalisation, using the RefFinder package. We defined a robust threshold of 'partial-protection’ with these genes and developed a strategy to simultaneously quantify matched host parasite burden and cytokine responses following immunisation or challenge. This is the first report systematically identifying reliable host reference genes for RTqPCR analysis following Plasmodium sporozoite challenge. A robust RTqPCR protocol incorporating reliable reference genes which enables simultaneous analysis of host whole-liver cytokine responses and parasite burden will significantly standardise and enhance results between international malaria vaccine efficacy studies.

Comparative transcriptome analysis between long- and short-term survival after pig-to-monkey cardiac xenotransplantation reveals differential heart failure development

ABSTRACT Cardiac xenotransplantation is the potential treatment for end-stage heart failure, but the allogenic organ supply needs to catch up to clinical demand. Therefore, genetically-modified porcine heart xenotransplantation could be a potential alternative. So far, pig-to-monkey heart xenografts have been studied using multi-transgenic pigs, indicating various survival periods. However, functional mechanisms based on survival period-related gene expression are unclear. This study aimed to identify the differential mechanisms between pig-to-monkey post-xenotransplantation long- and short-term survivals. Heterotopic abdominal transplantation was performed using a donor CD46-expressing GTKO pig and a recipient cynomolgus monkey. RNA-seq was performed using samples from POD60 XH from monkey and NH from age-matched pigs, D35 and D95. Gene-annotated DEGs for POD60 XH were compared with those for POD9 XH (Park et al. 2021). DEGs were identified by comparing gene expression levels in POD60 XH versus either D35 or D95 NH. 1,804 and 1,655 DEGs were identified in POD60 XH versus D35 NH and POD60 XH versus D95 NH, respectively. Overlapped 1,148 DEGs were annotated and compared with 1,348 DEGs for POD9 XH. Transcriptomic features for heart failure and inhibition of T cell activation were observed in both long (POD60)- and short (POD9)-term survived monkeys. Only short-term survived monkey showed heart remodeling and regeneration features, while long-term survived monkey indicated multi-organ failure by neural and hormonal signaling as well as suppression of B cell activation. Our results reveal differential heart failure development and survival at the transcriptome level and suggest candidate genes for specific signals to control adverse cardiac xenotransplantation effects.

PCa-Clf: A Classifier of Prostate Cancer Patients into Patients with Indolent and Aggressive Tumors Using Machine Learning

A critical unmet medical need in prostate cancer (PCa) clinical management centers around distinguishing indolent from aggressive tumors. Traditionally, Gleason grading has been utilized for this purpose. However, tumor classification using Gleason Grade 7 is often ambiguous, as the clinical behavior of these tumors follows a variable clinical course. This study aimed to investigate the application of machine learning techniques (ML) to classify patients into indolent and aggressive PCas. We used gene expression data from The Cancer Genome Atlas and compared gene expression levels between indolent and aggressive tumors to identify features for developing and validating a range of ML and stacking algorithms. ML algorithms accurately distinguished indolent from aggressive PCas. With the accuracy of 96%, the stacking model was superior to individual ML algorithms when all samples with primary Gleason Grades 6 to 10 were used. Excluding samples with Gleason Grade 7 improved accuracy to 97%. This study shows that ML algorithms and stacking models are powerful approaches for the accurate classification of indolent versus aggressive PCas. Future implementation of this methodology may significantly impact clinical decision making and patient outcomes in the clinical management of prostate cancer.

Identification of Two Flip-Over Genes in Grass Family as Potential Signature of C4 Photosynthesis Evolution.

In flowering plants, C4 photosynthesis is superior to C3 type in carbon fixation efficiency and adaptation to extreme environmental conditions, but the mechanisms behind the assembly of C4 machinery remain elusive. This study attempts to dissect the evolutionary divergence from C3 to C4 photosynthesis in five photosynthetic model plants from the grass family, using a combined comparative transcriptomics and deep learning technology. By examining and comparing gene expression levels in bundle sheath and mesophyll cells of five model plants, we identified 16 differentially expressed signature genes showing cell-specific expression patterns in C3 and C4 plants. Among them, two showed distinctively opposite cell-specific expression patterns in C3 vs. C4 plants (named as FOGs). The in silico physicochemical analysis of the two FOGs illustrated that C3 homologous proteins of LHCA6 had low and stable pI values of ~6, while the pI values of LHCA6 homologs increased drastically in C4 plants Setaria viridis (7), Zea mays (8), and Sorghum bicolor (over 9), suggesting this protein may have different functions in C3 and C4 plants. Interestingly, based on pairwise protein sequence/structure similarities between each homologous FOG protein, one FOG PGRL1A showed local inconsistency between sequence similarity and structure similarity. To find more examples of the evolutionary characteristics of FOG proteins, we investigated the protein sequence/structure similarities of other FOGs (transcription factors) and found that FOG proteins have diversified incompatibility between sequence and structure similarities during grass family evolution. This raised an interesting question as to whether the sequence similarity is related to structure similarity during C4 photosynthesis evolution.

Biomarkers associated with severity classification of asthma identified by comprehensive bioinformatics analysis

Using an integrated bioinformatics approach to find novel biomarkers that can predict asthma severity. From June 2022 to December 2022, this clinical medical study was conducted and completed in the Department of Allergy, Zhongnan Hospital of Wuhan University. The gene chip dataset GSE43696 was screened and downloaded from the high-throughput Gene Expression Omnibus (GEO) database, and the gene chip data preprocessing was completed using package "affy" in R and "rma" algorithm in turn. Use the the "edgeR" and "limma" packages to screen out the differentially expressed genes (DEGs) between normal controls, mild to moderate asthma patients and severe asthma patients, and then use the "clusterProfiler" package to perform GO enrichment analysis and KEGG pathway enrichment analysis of DEGs, finally use the STRING website to construct a protein-protein interaction (PPI) network of DEGs to further screen key genes. Using the R language "WGCNA" package, the weighted gene co-expression network analysis (WGCNA) was performed on the dataset GSE43696, and the modules significantly related to the severity of asthma were screened out, then the hub genes were obtained by intersecting the WGCNA analysis results with the DEGs screened by PPI. Datasets GSE43696 and GSE63142 were used to verify the expression of hub genes, and the diagnostic value was evaluated according to the ROC curve, then the potential function of hub genes in dataset GSE43696 was further clarified by gene set enrichment analysis (GSEA). The results showed that a total of 251 DEGs were screened, including 39 in the normal group and mild to moderate asthma group, 178 in the normal group and severe asthma group, and 34 in the mild to moderate asthma group and severe asthma group, mainly involved in biological processes such as response to toxic substance, response to oxidative stress, extracellular structure organization, extracellular matrix organization. Two modules significantly correlated with asthma severity were screened out (red module, P=7e-6, r=0.43; pink module, P=5e-8, r=-0.51), and finally six hub genes were obtained, including B3GNT6, CEACAM5, CCK, ERBB2, CSH1 and DPPA5. The comparison of gene expression levels and ROC curve analysis of datasets GSE43696 and GSE63142 further verified the six hub genes, which may associated with o-glycan biosynthesis, alpha linolenic acid metabolism, linoleic acid metabolism, pentose and glucoronate interconversions. In conclusion, through a variety of bioinformatics analysis methods, this study identified six hub genes significantly related to the severity of asthma, which potentially provided a new direction for the prediction and targeted therapy of asthma.

Comparative transcriptome analysis of different tissues of Solanum khasianum reveals candidate genes involved in steroidal glycoalkaloid biosynthesis.

Fruits and leaves of Solanum khasianum C. B. Clarke have long been used as a common Chinese herbal medicine. Steroidal glycoalkaloids (SGAs), the main active ingredient in S. khasianum, exhibit various pharmacological effects. However, genes involved in the SGA biosynthetic pathway in S. khasianum have not yet been identified. Genes encoding potential key SGA biosynthesis enzymes were identified through comprehensive RNA sequencing analysis (RNA-seq) of S. khasianum leaves, stems, and fruits. A total of 123,704 unigenes were obtained, of which 109,775 (88.74%) were annotated in seven public databases. Among these, 54 unigenes potentially involved in SGA biosynthesis were identified. Additionally, 23,636 differentially expressed genes were identified by comparing gene expression levels among the fruits, stems, and leaves of S. khasianum. The structural characteristics and phylogenetic relationship of cycloartenol synthase involved in SGA biosynthesis were further analyzed. Solasodine constituent was detected by high-performance liquid chromatography. This is the first study to report the comparative transcriptome analysis of different tissues of S. khasianum that identifies valuable genes potentially involved in SGA biosynthesis in this species.

Comparative Transcriptome Analysis Reveals Differential Gene Expression Pattern Associated with Heat Tolerance in Pepper (Capsicum annuum L.)

Pepper (Capsicum annuum L.) represents a highly significant agricultural commodity worldwide. Heat stress (HS) poses a severe threat to pepper productivity and quality. However, our understanding of the molecular alterations triggered by HS remains insufficient. This study focused on characterizing P19055 and P17087 as heat-tolerant and heat-sensitive pepper lines, respectively. Through RNA sequencing, we quantified transcript abundance in pepper fruit to investigate the impact of HS on gene expression. A total of 41,793 differentially expressed genes (DEGs) was identified, encompassing 33,703 known genes and 8090 novel genes. Additionally, we obtained 89,821 expressed transcripts, including 52,726 known transcripts and 37,095 new transcripts. By comparing gene expression levels between P17087 and P19055 fruit, we pinpointed 2324 genes exhibiting differential expression across three time points (0.5 h, 2 h, 6 h). Leveraging the weighted correlation network analysis (WGCNA) approach, we constructed a co-expression network of DEGs in P19055 and P17087 based on transcriptomic data acquired at these time points. Notably, nineteen modules displayed significant correlations with the time points following HS during the fruiting stage in both genotypes. Functional enrichment analysis revealed that the DEGs were primarily associated with metabolic and cellular processes in response to stress, particularly photosynthesis at the 2 h and 6 h time points. Moreover, we identified and categorized 26 families of transcription factors, including ERF (19), WRKY (12), MYB (15), NAC (7), bHLH (7), MIKC (7), GRAS (6), and 40 others, which may potentially regulate the expression of key genes in response to HS. Our findings contribute to a comprehensive understanding of the molecular mechanisms governing HS during the fruiting stage of pepper cultivation.

Abstract 5: Activation of PKA Signaling: A Milestone Associated With Bone Progression of Prostate Cancer

Abstract Purpose: Metabolic rewiring is critical for the adaptation of tumor cells to the new homing organ. We sought to identify metabolic dysregulations fueling PCa bone metastasis, modulated by bone secreted factors. Methods: By an indirect co-culture system of PCa (PC3) and bone progenitor cells (MC3T3, pre-osteoblasts, or Raw264.7, pre-osteoclasts), we assessed the transcriptome of PC3 cells modulated by soluble factors released by bone precursors. We validated the transcriptional profile of metabolic genes using open-access transcriptomic datasets. We performed an Ingenuity Pathway Analysis (IPA) to delineate the regulators of these metabolic genes. The bone secretome was profiled in the conditioned media (CM) by ESI-MS/MS. We validated our results using a PDX pre-clinical model comparing gene expression levels in MDA-PCa-183 growing intrafemorally (i.f.) vs. subcutaneously (s.c.). Results: PC3 cells co-cultured with bone progenitors displayed an activation of lipid metabolism, including the PPAR-signaling and fat absorption/digestion pathways. Accordingly, we observed an accumulation of neutral lipids in PC3 cells treated with the CM from the co-culture (Bodipy 493/503 staining). Unsupervised Clustering analysis using transcriptomic data from human PCa and bone metastatic samples (GSE74685) showed that the metabolic genes deregulated in co-cultured PC3 accurately clustered samples in primary tumor or bone metastasis. Moreover, 5 lipid-associated genes, PPARA, VDR, SLC16A1, PAPSS2 and GPX1, were associated with a 23-fold higher risk of death (SU2C-PCF dataset). This expression signature was validated in a PDX pre-clinical model when comparing MDA-PCa-183 growing i.f. vs. s.c. An IPA revealed that these genes are regulated by the Protein Kinase A (PKA). Accordingly, PKA inhibition led to a downregulation of these genes. Moreover, GSEA showcased an activation of PKA signaling pathways in MDA-PCa-183 i.f. vs. s.c., reinforcing the fact that the bone environment shapes PCa metabolism. Additionally, secretome and protein-protein interaction analyses revealed soluble factors (Col1a1, Fn1, etc.) secreted by bone cells that could regulate PKA activity. Conclusion: We identified a novel lipid-associated gene signature important for metastatic PCa, triggered by the dialogue with bone cells. This signature is under the regulation of PKA in response to bone-secreted factors, emerging as a potential target for intervention. Citation Format: Pablo Sanchis, Nicolas Anselmino, Sofia Lage-Vickers, Agustina Sabater, Rosario Lavignolle, Estefania Labanca, Peter Shepherd, Juan Bizzotto, Gaston Pascual, Rocio Seniuk, Ayelen Toro, Antonina Mitrofanova, Pia Valacco, Nora Navone, Javier Cotignola, Elba Vazquez, Geraldine Gueron. Activation of PKA Signaling: A Milestone Associated With Bone Progression of Prostate Cancer [abstract]. In: Proceedings of the 11th Annual Symposium on Global Cancer Research; Closing the Research-to-Implementation Gap; 2023 Apr 4-6. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(6_Suppl):Abstract nr 5.

Functional and comparative analysis of THI1 gene in grasses with a focus on sugarcane.

De novo synthesis of thiamine (vitamin B1) in plants depends on the action of thiamine thiazole synthase, which synthesizes the thiazole ring, and is encoded by the THI1 gene. Here, we investigated the evolution and diversity of THI1 in Poaceae, where C4 and C3 photosynthetic plants co-evolved. An ancestral duplication of THI1 is observed in Panicoideae that remains in many modern monocots, including sugarcane. In addition to the two sugarcane copies (ScTHI1-1 and ScTHI1-2), we identified ScTHI1-2 alleles showing differences in their sequence, indicating divergence between ScTHI1-2a and ScTHI1-2b. Such variations are observed only in the Saccharum complex, corroborating the phylogeny. At least five THI1 genomic environments were found in Poaceae, two in sugarcane, M. sinensis, and S. bicolor. The THI1 promoter in Poaceae is highly conserved at 300 bp upstream of the start codon ATG and has cis-regulatory elements that putatively bind to transcription factors associated with development, growth, development and biological rhythms. An experiment set to compare gene expression levels in different tissues across the sugarcane R570 life cycle showed that ScTHI1-1 was expressed mainly in leaves regardless of age. Furthermore, ScTHI1 displayed relatively high expression levels in meristem and culm, which varied with the plant age. Finally, yeast complementation studies with THI4-defective strain demonstrate that only ScTHI1-1 and ScTHI1-2b isoforms can partially restore thiamine auxotrophy, albeit at a low frequency. Taken together, the present work supports the existence of multiple origins of THI1 harboring genomic regions in Poaceae with predicted functional redundancy. In addition, it questions the contribution of the levels of the thiazole ring in C4 photosynthetic plant tissues or potentially the relevance of the THI1 protein activity.