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PubMed2026

Identification and characterization of G protein-coupled receptors in the nocturnal halictid bee Megalopta genalis.

G protein-coupled receptors (GPCRs) are one of the largest families of membrane proteins in insects, regulating vision, neural signal transduction, and various physiological behaviors. Megalopta genalis exhibits a unique facultatively eusocial lifestyle and possesses adaptations for nocturnal activity; however, its GPCR family has not yet been systematically characterized. In this study, we performed genome-wide identification, phylogenetic analysis, and expression profiling of GPCRs in M. genalis by integrating genomic annotation and transcriptomic analysis. The results showed that a total of 99 GPCRs were identified in the genome of M. genalis, which were classified into four major families. Here, we show that M. genalis has undergone lineage-specific GPCR repertoire remodeling, marked by the expansion of novel orphan receptors and the systematic loss of multiple receptor subtypes, such as the neuropeptide receptors MIP-R and NPFR. Moreover, opsins have formed a diverse array of combinations and non-GPCR odorant receptors have undergone significant expansion via tandem duplication. Together, these features may represent part of the molecular repertoire associated with the adaptation of M. genalis to a nocturnal lifestyle. Furthermore, transcriptomic analysis revealed distinct spatiotemporal expression divergence within each of the Mth/Mthl and Fz GPCR families, suggesting functional specialization across development and adult tissues. This study provides the first systematic identification and initial functional characterization of GPCRs in M. genalis, revealing an evolutionary pattern characterized by the coexistence of contraction and expansion within the GPCR family. These findings lay a foundation for further studies aimed at elucidating the roles of these GPCRs in regulating M. genalis physiology and behavior.

Animals↗
PubMed2026

Genome-wide epigenomic atlas and multi-omics responses of Eriocheir sinensis to natural extreme heat.

BACKGROUND: Global climate warming has led to increasingly frequent and prolonged extreme summer heat events, posing severe environmental challenges to aquaculture systems. Extreme summer heat can disrupt the performance of pond-cultured ectotherms. The Chinese mitten crab (Eriocheir sinensis) is an economically important freshwater crustacean, but coordinated molecular differences following contrasting natural summers remain incompletely characterized. RESULTS: We performed a comprehensive multi-omics analysis integrating meteorological monitoring, mRNA/lncRNA transcriptomics, small-RNA profiling of miRNAs, DNA methylomics, and LC-MS metabolomics in E. sinensis populations collected from Yancheng, China, between 2020 and 2024. Across the ten farms, survival was significantly lower in 2024, whereas yield and the proportion of large individuals showed nonsignificant downward trends. Gene-set analyses showed negative enrichment of cellular heat-response, protein-folding, oxidative-phosphorylation, and mitochondrial ATP-production terms in the 2024 cohort at the time of sampling. The integrated transcript annotation contained 72,240 lncRNAs and 63,833 mRNAs, and CpG was the predominant methylation context. Differential methylation analysis identified 73 regions and 185 cytosines, with hypomethylated events predominating within the significant subset. Metabolomic profiles differed between annual cohorts and mapped to carbohydrate, lipid, and amino-acid pathways. Cross-omics integration prioritized eight candidate genes-ADCY9, UNC79, UBN1, IFT52, ACO2, LOC126986070, LOC127001126, and LOC126997895-and qPCR reproduced the reported directions of expression for selected RNAs. CONCLUSION: This study provides the first integrative multi-omics framework for understanding chronic heat adaptation in E. sinensis. By linking transcriptomic, epigenomic, and metabolic remodeling, we elucidate the molecular mechanisms underlying energy imbalance, epigenetic reprogramming, and immune dysregulation during prolonged thermal stress. These findings offer valuable insights and genomic resources for breeding heat-tolerant crab strains and improving aquaculture resilience under ongoing climate change.

DNA methylation↗
PubMed2005

Use of 'Omic' technologies to study humans exposed to benzene.

'Omic' technologies include genomics, transcriptomics (gene expression profiling), proteomics and metabolomics. We are utilizing these new technologies in an effort to develop novel biomarkers of exposure, susceptibility and response to benzene. Advances in genomics allow one to study hundreds to thousands of single nucleotide polymorphisms simultaneously on small quantities of DNA using array-based technologies. We are currently utilizing these technologies to examine genetic variation in pathways relating to biotransformation, DNA repair, folate metabolism and immune response with the goal of finding biomarkers of susceptibility to benzene hematotoxicity. Transcriptomics is used to measure the full complement of activated genes, mRNAs or transcripts in a particular tissue at a particular time typically using microarray technology. We have applied microarrays to the study of global gene expression in the peripheral blood cells of benzene-exposed workers. More than 100 genes were identified as being potentially differentially expressed, with genes related to apoptosis and immune function being the most significantly affected. Initial studies employing proteomics have also shown that several proteins are altered in the serum of exposed compared to control subjects and these proteins are potential biomarkers of benzene exposure. Omic technologies therefore have significant potential in generating novel biomarkers of exposure, susceptibility and response to benzene.

Air Pollutants, Occupational↗
PubMed2026

Genome-scale perturb-seq in primary human CD4+ T cells maps context-specific regulators of T cell programs and human immune traits.

Gene regulatory networks encode the fundamental logic of cellular functions, but systematic network mapping remains challenging, especially in cell states relevant to human biology and disease. Here, we perturbed all expressed genes across 22 million primary human CD4+ T cells from four donors and developed a probe-based perturb-seq platform to measure the transcriptome effects in cells at rest and after stimulation. These data allowed us to map genes regulating immune pathways, including previously uncharacterized regulators of cytokine production. Importantly, active regulators and the gene programs they control changed dramatically across stimulation conditions. Perturbation signatures enabled us to model T cell states observed in population-scale transcriptomic atlases, nominating regulators of T cell polarization and of age-related phenotypes. Finally, we leveraged perturb-seq to implicate context-specific gene regulatory pathways in autoimmune disease risk. Our study provides a foundational resource and new approaches to decode T cell function and human immune traits.

CD4(+) T cell polarization↗
PubMed2026

GBFN: A gated bimodal fusion network leveraging foundation model embeddings for cancer drug sensitivity prediction.

Despite recent progress in deep learning for cancer drug sensitivity prediction, many existing models still rely on task-specific representation learning or relatively simple multimodal fusion, which may limit their ability to capture complex drug-cell interactions. To address this issue, we developed GBFN, a gated bimodal fusion network for continuous IC50 prediction that integrates pretrained drug and cell-line representations. Specifically, drug embeddings were obtained from SMI-TED, whereas cell-line embeddings were derived from transcriptomic profiles using BulkFormer. These two modalities were then combined through a dimension-wise gated fusion module and used to predict IC50 values in matched drug-cell line pairs. On the CCLE-based benchmark, GBFN outperformed representative neural baselines, including GraphDRP, TGSA, and TransEDRP, and achieved the best overall performance, with an R² of 0.8714 and an RMSE of 0.8938. Moreover, ablation analysis showed that the model using drug features and cell-line expression data with gated fusion performed better than the corresponding model using direct concatenation, indicating that the improvement was associated with the fusion strategy rather than with the input modalities alone. In addition, cell-line expression data were more informative than mutation data in the present setting, and adding mutation data to the model using drug features and expression data did not further improve performance. Across major cancer types, GBFN maintained generally high cell-line-level predictive performance, and perturbation-based attribution identified biologically relevant transcriptomic programs in selected drug-cell line settings. Together, these findings support GBFN as a compact and effective framework for continuous drug response prediction.

Humans↗
PubMed2026

Machine learning-enabled multi-omics discovery of prognostic biomarkers and signaling targets in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) remains difficult to subtype using single omics layers. We conducted an exploratory investigation integrating reverse-phase protein array (RPPA) and DNA methylation data from the cancer genome atlas (TCGA)- pancreatic adenocarcinoma (PAAD) to assess the feasibility of multi-omics subtyping, alongside a supervised machine learning analysis of a small gene expression omnibus (GEO) transcriptomic cohort (n = 26) to identify candidate diagnostic genes. RPPA-based K-means clustering suggested a weak, possible two-subtype structure (silhouette ≈ 0.16) that remained unassociated with overall survival (log-rank p = 0.113) and lacked independent prognostic value. An independently performed similarity network fusion (SNF) analysis integrating RPPA and methylation data showed low concordance with RPPA-derived subtypes (Adjusted Rand Index (ARI) = 0.014), indicating limited convergence between molecular modalities. Supervised machine learning analysis of the GEO cohort using a fully nested leave-one-out cross-validation pipeline achieved a mean (area under the curve) AUC of 0.896 across four classifiers and identified four-fold-stable candidate genes (ESCO2, COL17A1, BCL2L14, and SOWAHB). However, this gene panel demonstrated limited external validity across two independent PDAC cohorts (log-rank p = 0.438 for both GSE62452 and GSE28735), indicating limited generalizability despite robust internal performance. Collectively, these findings provide limited evidence for a robust, prognostically significant multi-omics subtype or a validated diagnostic gene signature; instead, this study serves as a hypothesis-generating resource and highlights the importance of rigorous cross-validation and independent external validation in small-sample transcriptomic biomarker discovery.

Humans↗
PubMed2026

Integrin α3 (ITGA3) expression across breast cancer subtypes: Prognosis and therapeutic relevance.

BACKGROUND: Integrin &#x3b1;3 (ITGA3), which heterodimerizes with integrin &#x3b2;1, has emerged as a potential biomarker and therapeutic target in several epithelial malignancies; however, its clinical relevance in breast cancer remains incompletely characterized. This study evaluated ITGA3 expression across breast cancer molecular subtypes and assessed its prognostic and predictive significance. METHODS: Immunohistochemistry (IHC) was performed on archival breast cancer specimens using tissue microarrays (n = 148) and whole-tissue sections (n = 21). Complete clinicopathologic and outcome data were available for 108 patients, including hormone receptor-positive/human epidermal growth factor receptor 2-negative, HER2-positive, and triple-negative breast cancer (TNBC) subtypes. ITGA3 expression was quantified using H-scores and correlated with clinicopathologic features and survival outcomes. Independent transcriptomic analyses were conducted using the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) and the Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) cohorts to evaluate ITGA3 mRNA expression, co-expressed signaling pathways, and associations with therapeutic response. RESULTS: ITGA3 protein expression was detected in 85.2% of breast cancer specimens and was significantly higher in HR-positive/HER2-negative and HER2-positive tumors compared with TNBC (p < 0.0050). High ITGA3 expression was associated with shorter recurrence-free survival (p < 0.0001). In the METABRIC cohort, tumors with ITGA3 alterations demonstrated significantly worse relapse-free survival (p < 0.0001) and overall survival (p < 0.0500). Transcriptomic analyses revealed that ITGA3 co-expressed with estrogen receptor 1(ESR1), erb-b2 receptor tyrosine kinase 2 (ERBB2), and luminal markers, along with enrichment of estrogen receptor and phosphoinositide 3-kinase-protein kinase B-mechanistic target of rapamycin (PI3K/AKT/mTOR) signaling pathways. ITGA3 expression was not predictive of response to tamoxifen or trastuzumab. CONCLUSION: Elevated ITGA3 expression is associated with breast cancer recurrence and poor clinical outcomes, supporting its potential role as a prognostic biomarker and candidate therapeutic target.

Biomarkers↗
PubMedDate not supplied

ORESTES are enriched in rare exon usage variants affecting the encoded proteins.

A significant fraction of the variability found in the human transcriptome is due to alternative splicing, including alternative exon usage (AEU), intron retention and use of cryptic splice sites. We present a comparison of a large-scale analysis of AEU in the human transcriptome through genome mapping of Open Reading Frame ESTs (ORESTES) and conventional ESTs. It is shown here that ORESTES probe low abundant messages more efficiently. In addition, most of the variants detected by ORESTES affect the structure of the corresponding proteins.

Alternative Splicing↗
PubMed2006

Anti-oxidant sensitivity of donor age-related gene expression in cultured fibroblasts.

Cultured human fibroblasts display age-dependent transcriptomic differences. We hypothesized that aging-associated oxidative stress affects gene expression, and monitored the transcriptome in confluent fibroblasts from young and old individuals cultured without and with a lipophilic and hydrophilic anti-oxidant mixture (vitamin E, quercetin, hydroxytyrosol and kaempferol). In cells derived from old subjects genes with lower expression were related to oxidative stress, growth and differentiation, cell cycle or metabolic enzymes and with higher expression to protein processing and docking, extracellular matrix, immune response, EGF-signalling and transcription. Anti-oxidant treatment modulated a similar number of genes in all donors and induced cell cycle regulatory genes. A subset of genes, modulated by age and inversely modulated by anti-oxidants, included glutaminase. Despite increased glutaminase expression, donor age-dependent decline in glutathione content and resistance to glutathione-depletion was observed. Summarizing, gene expression of fibroblasts is affected by donor age and a subset was corrected by anti-oxidants. Thus, in cultured fibroblasts from aged donors, gene expression is partly driven by oxidative stress.

Adolescent↗
PubMed2025

Liquid Biopsy-Multiomics Link Adhesion Pathway Dysregulation to Kidney Injury Severity.

INTRODUCTION: Severe acute kidney injury (AKI) is strongly associated with the risk of developing chronic kidney disease; however, little is known about the cell type-specific mechanisms driving kidney injury severity. METHODS: In this multicenter observational study, we used clinically obtained liquid biopsy proteomics and machine learning (ML) to predict severe outcomes in patients with COVID-associated and non-COVID AKI. Further, we orthogonally combined 169 urine proteomics with 437 plasma proteomics samples and 40 urine sediment single-cell transcriptomics samples to identify complementary dysregulated mechanisms. RESULTS: Using a 10-fold cross-validated random forest algorithm, we identified a set of urinary proteins that demonstrate predictive power for both discovery and validation set with AUC of 87% and 76%, respectively. These predictive proteomics features obtained demonstrate that cell adhesion and autophagy-associated pathways are uniquely impacted in severe AKI. Differentially abundant proteins (DAPSs) associated with these pathways are highly expressed in cells of the juxtamedullary nephron, endothelial cells (ECs), and podocytes, indicating that these kidney cell types could be potential targets. Single-cell transcriptomic analysis in the in vitro model of kidney organoids infected with SARS-CoV-2 reveal dysregulation of extracellular matrix (ECM) organization in multiple nephron segments, recapitulating the clinically observed fibrotic response across multiomics datasets. Ligand-receptor interaction analysis of the podocyte and tubule organoid clusters shows significant reduction and loss of interaction between integrins and basement membrane receptors in the infected kidney organoids. CONCLUSION: Collectively, these data suggest that ECM degradation and adhesion-associated mechanisms could be the main driver of severe kidney injury.

AKI↗
PubMed2026

Cerium dioxide nanoparticle exposure attenuates mobility-linked antibiotic resistome signatures across the soil-lettuce continuum.

Antibiotic resistance genes (ARGs) are contaminants of emerging concern in agricultural microbiomes. Their association with mobile genetic elements (MGEs) can enhance dissemination across soil-plant interfaces, creating potential environmental and food-chain exposure risks. However, how engineered nanoparticles modulate relative ARG abundance and mobility-linked resistome features in plant-associated microbiomes remains poorly understood. Here, we examined the effects of graded, experimentally elevated cerium dioxide nanoparticle (CeO2 NP) loadings in a soil-lettuce system by integrating compartment-resolved metagenomics, ARG-MGE co-occurrence analysis, putative host-reservoir profiling, transcriptomics, and functional assays. Metagenomic profiling identified 16 ARG types and 125 subtypes and revealed niche-dependent microbiome restructuring under CeO2 NP exposure. Rhizosphere relative ARG abundance showed a negative dose-associated trend, although overall inter-group differences were not significant, whereas leaf endophytes showed a weaker response. Relative MGE abundance decreased significantly in both compartments, and lower assembly-level ARG-MGE co-occurrence reflected fewer ARGs detected in MGE-associated genomic contexts, whereas fewer multi-ARG contigs suggested reduced ARG clustering and potential co-selection. Putative host-reservoir analysis associated key efflux determinants with bacterial families whose relative representation declined following CeO2 NP exposure. Transcriptomic profiling of representative putative ARG hosts revealed host-specific responses, including downregulation of genes involved in central metabolism and Sec-dependent trafficking. Complementary host assays showed reduced apparent envelope permeability and lower recovery of tetracycline-resistant recipient-identity colonies in the plasmid-associated host system. Together, under the tested elevated-loading conditions, CeO2 NP exposure was associated with lower relative ARG signals and weaker mobility-linked resistome features across the soil-lettuce continuum, providing mechanistic insight into nanoparticle-resistome interactions in soil-plant systems.

ARG dissemination↗
PubMed2006

A cDNA-AFLP based strategy to identify transcripts associated with avirulence in Phytophthora infestans.

Expression profiling using cDNA-AFLP is commonly used to display the transcriptome of a specific tissue or developmental stage. Here, cDNA-AFLP was used to identify transcripts in a segregating F1 population of Phytophthora infestans, the oomycete pathogen that causes late blight. To find transcripts derived from putative avirulence (Avr) genes germinated cyst cDNA from F1 progeny with defined avirulence phenotypes was pooled and used in a bulked segregant analysis (BSA). Over 30,000 transcript derived fragments (TDFs) were screened resulting in 99 Avr-associated TDFs as well as TDFs with opposite pattern. With 142 TDF sequences homology searches and database mining was carried out. cDNA-AFLP analysis on individual F1 progeny revealed 100% co-segregation of four TDFs with particular AVR phenotypes and this was confirmed by RT-PCR. Two match the same P. infestans EST with unknown sequence and this is a likely candidate for Avr4. The other two are associated with the Avr3b-Avr10-Avr11 locus. This combined cDNA-AFLP/BSA strategy is an efficient approach to identify Avr-associated transcriptome markers that can complement positional cloning.

Chromosome Mapping↗
PubMed2006

Venom gland EST analysis of the saw-scaled viper, Echis ocellatus, reveals novel alpha9beta1 integrin-binding motifs in venom metalloproteinases and a new group of putative toxins, renin-like aspartic proteases.

Echis ocellatus is the most medically important snake in West Africa. However, the composition of its venom and the differential contribution of these venom components to the severe haemorrhagic and coagulopathic pathology of envenoming are poorly understood. To address this situation we assembled a toxin transcriptome based upon 1000 expressed sequence tags (EST) from a cDNA library constructed from pooled venom glands of 10 individual E. ocellatus. We used a variety of bioinformatic tools to construct a fully annotated venom-toxin transcriptome that was interrogated with a combination of BLAST annotation, gene ontology cataloguing and disintegrin-motif searching. The results of these analyses revealed an unusually abundant and diverse expression of snake venom metalloproteinases (SVMP) and a broad toxin-expression profile including several distinct isoforms of bradykinin-potentiating peptides, phospholipase A(2), C-type lectins, serine proteinases and l-amino oxidases. Most significantly, we identified for the first time a conserved alpha(9)beta(1) integrin-binding motif in several SVMPs, and a new group of putative venom toxins, renin-like aspartic proteases.

Amino Acid Motifs↗
PubMed2025

Deleterious, protein-altering variants in GSPT2 are putatively associated with an X-linked neurodevelopmental disorder with intellectual disability, language impairment, autism, and epilepsy.

PURPOSE: Approximately 6% of individuals with neurodevelopmental disorders are predicted to be X-linked, and the GSPT2 gene, located at Xp11.22, has not yet been associated with any Mendelian disease. METHODS: To establish genotype-phenotype associations between GSPT2 and neurodevelopmental disorders, clinical investigations were performed in unrelated individuals, genomic and functional studies were conducted on the participants' blood and heterologous cell system. RESULTS: We described 6 individuals from 6 unrelated families carrying hemizygous variants in GSPT2 with intellectual disability, delayed speech and language development, autism spectrum disorder, epilepsy, or abnormal fetal neurodevelopment. Structural molecular modeling revealed significant deleterious effects of the identified variants. GSPT2 is preferentially enriched in the brain and cerebellum compared with other tissues. GSPT2-deficient H4 neuroglioma cells slow down the proliferation and downregulate the expression of cell-cycle-related genes. Transcriptomics revealed that GABAergic and calcium-signaling-related genes were significantly downregulated in GSPT2-deficient cells. Consistent with the transcriptomic data, RT-PCR analysis verified the marked downregulation of critical genes (CACNA1B, etc) in GSPT2-knockout cells and further confirmed these findings with proteomic profiling. CONCLUSION: Our data suggest a putative GSPT2-related X-linked neurodevelopmental disorders through dysregulation of cell-cycle progression and calcium/GABAergic signaling pathways.

Humans↗
PubMed2005

Global gene expression analysis of Anopheles gambiae responses to microbial challenge.

Anopheles gambiae transcript responses to experimental challenge with heat inactivated Salmonella typhimurium, Staphylococcus aureus and Beauveria bassiana have been analyzed with an Affymetrix GeneChip comprising the entire predicted mosquito transcriptome. Significant up- or down-regulation (greater than 2-fold) can be assayed for approximately 2% of the mosquito transcriptome and affected genes represent a variety of functional classes that include immunity, apoptosis, stress response, detoxification, metabolism, blood digestion, olfaction and others. Transcript responses to the 3 microbial elicitors exhibit an exceptionally high degree of specificity and only a few genes are significantly regulated by more than 1 of the tested elicitors. This study identifies several transcripts that have not been linked directly to immune response in A. gambiae previously; their infection responsiveness and sequence features do however suggest implication in defence reactions; examples are genes encoding leucine-rich repeat domain proteins, cuticle domain proteins and proteins containing immunoglobulin and fibronectin domains.

Animals↗
PubMed2026

Ecr positively regulates activity of the PhoQ/PhoP signalling system in Klebsiella pneumoniae.

BACKGROUND: The rising prevalence of polymyxin resistance in multidrug-resistant Klebsiella pneumoniae presents a critical situation with limited therapeutic options. METHODS: Methods Genomic sequencing of 15 clinical polymyxin-resistant K. pneumoniae strains with multidrug resistance revealed that MgrB inactivation, predominantly disrupted by insertion sequences (ISs) in the IS1, IS4, and IS5 families, was the leading cause of polymyxin resistance. Comparative transcriptomics of wild-type, &#x394;mgrB, and &#x394;mgrB&#x394;phoP were performed to elucidate the MgrB-PhoPQ regulatory network. RESULTS: This study conducted a system-wide analysis of the regulatory network and identified a species-specific PhoPQ regulon in K. pneumoniae.Beyond the classical MgrB-PhoPQ-ArnBCADTEF pathway, we identified a previously unannotated PhoPQ-regulated gene, 144 bp LN739_RS09850, encoding an Ecr homologue from Enterobacter cloacae. This protein has been reported to confer colistin heteroresistance, with the underlying mechanism not yet functionally validated. This study revealed that overexpression of Ecr homologues decreased colistin susceptibility in both K. pneumoniae and E. cloacae, but this phenotype was abolished upon phoP deletion, confirming PhoP's essential role. Consistent with this dependency, comparative transcriptomics of Ecr-overexpressing K. pneumoniae vs. control revealed significant upregulation of mgrB, phoPQ, arnBCADTE, and pmrD. Two-hybrid bacterial assays further demonstrated direct Ecr-PhoQ interaction. Electrophoretic mobility shift assay confirmed that PhoP directly binds to the ecr promoter in vitro, and a &#x3b2;-galactosidase reporter assay demonstrated that PhoP enhanced ecr promoter activity, indicating that PhoP regulates ecr expression by directly controlling its transcription. CONCLUSION: Collectively, these findings suggest that PhoP may directly activate the transcription of Ecr, with Ecr feedback activating the PhoPQ system via interaction with PhoQ, leading to induction of the arn operon and consequent polymyxin resistance.

Klebsiella pneumoniae↗
PubMed2006

Identification and analysis of genes expressed in the adult filarial parasitic nematode Dirofilaria immitis.

The heartworm Dirofilaria immitis is a filarial parasitic nematode infecting dogs and other mammals worldwide causing fatal complications. Here, we present the first large-scale survey of the adult heartworm transcriptome by generation and analysis of 4005 expressed sequence tags, identifying about 1800 genes and expanding the available sequence information for the parasite significantly. Brugia malayi genomic data offered the most valuable information to interpret heartworm genes, with about 70% of D. immitis genes showing significant similarities to the assembly. Comparative genomic analyses revealed both genes common to metazoans or nematodes and genes specific to filarial parasites that may relate to parasitism. Characterization of abundant transcripts suggested important roles for genes involved in energy generation and antioxidant defense in adults. In particular, we proposed that adult heartworm likely adopted an anaerobic electron transfer-based energy generation system distinct from the aerobic pathway utilized by its mammalian host, making it a promising target in developing next generation macrofilaricides and other treatments. Our survey provided novel insights into the D. immitis transcriptome and laid a foundation for further comparative studies on biology, parasitism and evolution within the phylum Nematoda.

Animals↗
PubMed2006

Dioecious Schistosoma mansoni express divergent gene repertoires regulated by pairing.

Pairing of adult Schistosoma mansoni parasites initiates a cascade of events including mating and egg production that ultimately leads to immuno-pathological lesions during schistosomiasis. To identify genes associated with this important biological process, we studied parasites isolated from single- versus mixed-sex cercariae-infected mice using DNA microarray analysis to uncover pair-regulated transcriptional profiles. We report that: (i) transcriptomes of parasites isolated from single-sex infections are significantly more complex than their mixed-sex counterparts; (ii) transcriptomes of single-sex males are distinct from mixed-sex males; and (iii) not all transcripts, previously hypothesized to be critical in female egg production, are regulated by pairing.

Animals↗

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