Oxidation-reduction process of Arabidopsis thaliana roots induced by bisphenol compounds based on RNA-seq analysis.

Bisphenol compounds (BPs) have various industrial uses and can enter the environment through various sources. To evaluate the ecotoxicity of BPs and identify potential gene candidates involved in the plant toxicity, Arabidopsis thaliana was exposed to bisphenol A (BPA), BPB, BPE, BPF, and BPS at 1, 3, 10 mg/L for a duration of 14 days, and their growth status were monitored. At day 14, roots and leaves were collected for internal BPs exposure concentration detection, RNA-seq (only roots), and morphological observations. As shown in the results, exposure to BPs significantly disturbed root elongation, exhibiting a trend of stimulation at low concentration and inhibition at high concentration. Additionally, BPs exhibited pronounced generation of reactive oxygen species, while none of the pollutants caused significant changes in root morphology. Internal exposure concentration analysis indicated that BPs tended to accumulate in the roots, with BPS exhibiting the highest level of accumulation. The results of RNA-seq indicated that the shared 211 differently expressed genes (DEGs) of these 5 exposure groups were enriched in defense response, generation of precursor metabolites, response to organic substance, response to oxygen-containing, response to hormone, oxidation-reduction process and so on. Regarding unique DEGs in each group, BPS was mainly associated with the redox pathway, BPB primarily influenced seed germination, and BPA, BPE and BPF were primarily involved in metabolic signaling pathways. Our results provide new insights for BPs induced adverse effects on Arabidopsis thaliana and suggest that the ecological risks associated with BPA alternatives cannot be ignored.

Acute exposure to mercury drives changes in gene expression in Drosophila melanogaster.

OBJECTIVE: We quantified the effect of acute exposure to a high dosage of inorganic mercury on gene expression in Drosophila melanogaster using RNA-sequencing of whole adult females. RESULTS: We found 119 genes with higher gene expression following treatment (including all 5 Drosophila metallothionine genes and a number of heat shock protein genes), and 31 with lower expression (several of which are involved in egg formation). Our results highlight biological processes and genetic pathways impacted by exposure to this toxic metal, and provide motivation for future studies to understand the genetic basis of response to mercury.

scPanel: a tool for automatic identification of sparse gene panels for generalizable patient classification using scRNA-seq datasets.

Single-cell RNA sequencing (scRNA-seq) technologies can generate transcriptomic profiles at a single-cell resolution in large patient cohorts, facilitating discovery of gene and cellular biomarkers for disease. Yet, when the number of biomarker genes is large, the translation to clinical applications is challenging due to prohibitive sequencing costs. Here, we introduce scPanel, a computational framework designed to bridge the gap between biomarker discovery and clinical application by identifying a sparse gene panel for patient classification from the cell population(s) most responsive to perturbations (e.g. diseases/drugs). scPanel incorporates a data-driven way to automatically determine a minimal number of informative biomarker genes. Patient-level classification is achieved by aggregating the prediction probabilities of cells associated with a patient using the area under the curve score. Application of scPanel to scleroderma, colorectal cancer, and COVID-19 datasets resulted in high patient classification accuracy using only a small number of genes (<20), automatically selected from the entire transcriptome. In the COVID-19 case study, we demonstrated cross-dataset generalizability in predicting disease state in an external patient cohort. scPanel outperforms other state-of-the-art gene selection methods for patient classification and can be used to identify parsimonious sets of reliable biomarker candidates for clinical translation.

Epigenomic and transcriptomic profiling of solitary fibrous tumors identifies site-specific patterns and candidate genes regulated by DNA methylation.

Solitary fibrous tumor (SFT) is a rare mesenchymal neoplasm which can arise at any anatomic site and is characterized by recurrent NAB2::STAT6 fusions and metastatic progression in 10-30%. The cell of origin has not been identified. Despite some progress in understanding the contribution of heterogeneous fusion types and secondary mutations to SFT biology, epigenetic alterations in extrameningeal SFT remain largely unexplored, and most sarcoma research to date has focused on the use of methylation profiling for tumor classification. We interrogated genome-wide DNA methylation in 79 SFTs to identify informative epigenetic changes. RNA-seq data from targeted panels and data from the Cancer Genome Atlas (TCGA) were used for orthogonal validation of selected findings. In unsupervised clustering analysis, the top 500 most variable CpGs segregated SFTs by primary anatomic site. Differentially methylated genes (DMGs) associated with primary SFT site included EGFR, TBX15, multiple HOX genes and their cofactors EBF1, EBF3, and PBX1, as well as RUNX1 and MEIS1. Of the 20 DMGs that were interrogated on the RNA-seq panel, twelve were significantly differentially expressed according to site. However, with the exception of TBX15, most of these also showed differential expression according to NAB2::STAT6 fusion type, suggesting that the fusion oncogene contributes to transcriptional regulation of these genes. Transcriptomic data confirmed an inverse correlation between gene methylation and the expression of TBX15 in both SFT and TCGA sarcomas. TBX15 also showed differential mRNA expression and 5' UTR methylation between tumors located in different anatomic sites in TCGA data. In all analyses, TBX15 methylation and mRNA expression retained the strongest association with tissue of origin in SFT and other sarcomas, suggesting a possible marker to distinguish metastatic tumors from new primaries without genomic profiling. Epigenetic signatures may further help to identify SFT progenitor cells at different anatomic sites.

Molecular mechanisms underlying the effects of hypo- and hyper-prolactinemia on spermatogenesis and fertility in male rats.

PURPOSE: Hypo- and hyper-prolactinemia have deleterious effects on male reproduction, yet there is a dearth of information regarding the underlying mechanisms. The aim of this study was to delineate the molecular mechanisms by which hypo- and hyper-prolactinemia affects spermatogenesis and fertility in male rats. METHODS: In vivo male rat models for hypo- and hyper-prolactinemia were established using dopamine receptor agonist, Bromocriptine (Brm), and antagonist, Fluphenazine (Flu), respectively. Effects on fertility and spermatogenesis were assessed by studying pre- and post-implantation loss, litter size, sperm parameters, hormonal profile, testicular histology, testicular cell population, and testicular transcriptome in rats. RESULTS: Treatment with Brm and Flu for 60 days led to subfertility, which was indicated by an increase in pre- and post-implantation loss and decrease in litter size, when mated with control female rats. Decreased sperm count was observed after both treatments, whereas reduced sperm motility was noted in Flu group. Serum FSH was unaffected, and LH was decreased by Flu treatment. Testosterone was decreased in both the groups, whereas estradiol was decreased in the Flu group. An arrest in spermatogenic cycle beyond round spermatids was observed in the Flu group. Additionally, testicular apoptosis in germ cells, mostly spermatocytes of Stage IX-XIV was noted in both the groups. Further, testicular RNA-Seq analysis revealed a total of 1539 and 824 differentially expressed genes/DEGs in Brm and Flu, respectively (Sequence Read Archive/SRA Database accession number: PRJNA1150513). Gene ontology and pathway analysis of DEGs highlighted enrichment of steroid metabolic pathway and ribosomal biogenesis pathway. Hub genes identified from the DEGs were validated by qPCR and the results showed that Uba52, Rps27a, Rpl23, Rps5, Rps16 were significantly down-regulated by Brm, whereas Rps27a, Rps29, Rps15, Rps27, Faul1 were significantly down-regulated by Flu. CONCLUSION: Hypo- and hyper-prolactinemia leads to subfertility and decreased sperm parameters possibly through an effect on steroid metabolism and ribosomal biogenesis pathway. Therefore, maintaining prolactin levels in physiological range is crucial.

Transcriptome-based prediction for polygenic traits in rice using different gene subsets.

BACKGROUND: Transcriptome-based prediction of complex phenotypes is a relatively new statistical method that links genetic variation to phenotypic variation. The selection of large-effect genes based on a priori biological knowledge is beneficial for predicting oligogenic traits; however, such a simple gene selection method is not applicable to polygenic traits because causal genes or large-effect loci are often unknown. Here, we used several gene-level features and tested whether it was possible to select a gene subset that resulted in better predictive ability than using all genes for predicting a polygenic trait. RESULTS: Using the phenotypic values of shoot and root traits and transcript abundances in leaves and roots of 57 rice accessions, we evaluated the predictive abilities of the transcriptome-based prediction models. Leaf transcripts predicted shoot phenotypes, such as plant height, more accurately than root transcripts, whereas root transcripts predicted root phenotypes, such as crown root length, more accurately than leaf transcripts. Furthermore, we used the following three features to train the prediction model: (1) tissue specificity of the transcripts, (2) ontology annotations, and (3) co-expression modules for selecting gene subsets. Although models trained by a gene subset often resulted in lower predictive abilities than the model trained by all genes, some gene subsets showed improved predictive ability. For example, using genes expressed in roots but not in leaves, the predictive ability for crown root diameter was improved by more than 10% (R2 = 0.59 when using all genes; R2 = 0.66, using 1,554 root-specifically expressed genes). Similarly, genes annotated as "gibberellic acid sensitivity" showed higher predictive ability than using all genes for root dry weight. CONCLUSIONS: Our results highlight both the possibility and difficulty of selecting an appropriate gene subset to predict polygenic traits from transcript abundance, given the current biological knowledge and information. Further integration of multiple sources of information, as well as improvements in gene characterization, may enable the selection of an optimal gene set for the prediction of polygenic phenotypes.

SAE-Impute: imputation for single-cell data via subspace regression and auto-encoders.

BACKGROUND: Single-cell RNA sequencing (scRNA-seq) technology has emerged as a crucial tool for studying cellular heterogeneity. However, dropouts are inherent to the sequencing process, known as dropout events, posing challenges in downstream analysis and interpretation. Imputing dropout data becomes a critical concern in scRNA-seq data analysis. Present imputation methods predominantly rely on statistical or machine learning approaches, often overlooking inter-sample correlations. RESULTS: To address this limitation, We introduced SAE-Impute, a new computational method for imputing single-cell data by combining subspace regression and auto-encoders for enhancing the accuracy and reliability of the imputation process. Specifically, SAE-Impute assesses sample correlations via subspace regression, predicts potential dropout values, and then leverages these predictions within an autoencoder framework for interpolation. To validate the performance of SAE-Impute, we systematically conducted experiments on both simulated and real scRNA-seq datasets. These results highlight that SAE-Impute effectively reduces false negative signals in single-cell data and enhances the retrieval of dropout values, gene-gene and cell-cell correlations. Finally, We also conducted several downstream analyses on the imputed single-cell RNA sequencing (scRNA-seq) data, including the identification of differential gene expression, cell clustering and visualization, and cell trajectory construction. CONCLUSIONS: These results once again demonstrate that SAE-Impute is able to effectively reduce the droupouts in single-cell dataset, thereby improving the functional interpretability of the data.

Exploring the potential mechanism of Radix Bupleuri in the treatment of sepsis: a study based on network pharmacology and molecular docking.

AIM: To explore, using network pharmacology and RNA-seq technologies, potential active targets and mechanisms underpinning Radix Bupleuri's effectiveness during sepsis treatment. METHODS: Following the Sepsis-3.0 criteria, the research cohort, comprising 23 sepsis patients and 10 healthy participants, was obtained from public databases. Peripheral blood samples were collected and subjected to RNA-seq analysis. Active ingredients and potential targets of Radix Bupleuri were identified using the Bioinformatics Analysis Tool for Molecular mechANism of Traditional Chinese Medicine 2.0 (BATMAN-TCM 2.0) database and TCMSP database. Subsequently, protein-protein interaction (PPI) network construction, Gene Ontology (GO) analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were conducted to explore cross-targets between disease and drugs. Survival analysis of key targets was performed using the GSE65682 dataset, and single-cell RNA-seq was employed for cellular localization analysis of key genes. Finally, molecular docking and Molecular dynamics simulation of the core target was conducted. RESULTS: Differential expression analysis revealed 4253 genes associated with sepsis. Seventy-six active components and 1030 potential targets of Radix Bupleuri were identified. PPI, GO, and pathway enrichment analyses indicated involvement in the regulation of transmembrane transport, monatomic ion transport, and MAPK signaling. Survival curve analysis identified PIK3CD, ARRB2, SUCLG1, and SPI1 as key targets associated with lower mortality in the high expression group, while higher mortality was observed in the high PNP and FURIN expression groups. Single-cell RNA sequencing unveiled the cellular localization of PIK3CD, PNP, SPI1, and FURIN within macrophages, while ARRB2 and SUCLG1 exhibited localization in both macrophages and T-cells. Subsequent molecular docking and Molecular dynamics simulation indicated a potential binding interaction for Carvone-PIK3CD, Encecalin-ARRB2, Lauric Acid-SUCLG1, Pulegone-FURIN, Nootkatone-SPI1, and Saikogenin F-PNP. CONCLUSION: Radix Bupleuri could modulate immune function by affecting PIK3CD, ARRB2, SUCLG1, FURIN, SPI1, and PNP, thereby potentially improving the prognosis of sepsis.

Identification of functional heterogeneity of immune cells and tubular-immune cellular interplay action in diabetic kidney disease.

Background: Renal inflammation plays key roles in the pathogenesis of diabetic kidney disease (DKD). Immune cell infiltration is the main pathological feature in the progression of DKD. Sodium glucose cotransporter 2 inhibitor (SGLT2i) were reported to have antiinflammatory effects on DKD. While the heterogeneity and molecular basis of the pathogenesis and treatment with SGLT2i in DKD remains poorly understood. Methods: To address this question, we performed a single-cell transcriptomics data analysis and cell cross-talk analysis based on the database (GSE181382). The single-cell transcriptome analysis findings were validated using multiplex immunostaining. Results: A total of 58760 cells are categorized into 25 distinct cell types. A subset of macrophages with anti-inflammatory potential was identified. We found that Ccl3+ (S100a8/a9 high) macrophages with anti-inflammatory and antimicrobial in the pathogenesis of DKD decreased and reversed the dapagliflozin treatment. Besides, dapagliflozin treatment enhanced the accumulation of Pck1+ macrophage, characterized by gluconeogenesis signaling pathway. Cell-cross talk analysis showed the GRN/SORT1 pair and CD74 related signaling pathways were enriched in the interactions between tubular epithelial cells and immune cells. Conclusions: Our study depicts the heterogeneity of macrophages and clarifies a new possible explanation of dapagliflozin treatment, showing the metabolism shifts toward gluconeogenesis in macrophages, fueling the anti-inflammatory function of M2 macrophages, highlighting the new molecular features and signaling pathways and potential therapeutic targets, which has provided an important reference for the study of immune-related mechanisms in the progression of the disease.

Pediatric Sepsis - Sailing the Unchartered Waters with Omics.

How to cite this article: Baalaaji M. Pediatric Sepsis - Sailing the Unchartered Waters with Omics. Indian J Crit Care Med 2024;28(9):818-819.

JPH203 alleviates peritoneal fibrosis via inhibition of amino acid-mediated mTORC1 signaling.

BACKGROUND AND AIMS: The mesothelial-mesenchymal transition (MMT) of mesothelial cells has been recognized as a critical process during progression of peritoneal fibrosis (PF). Despite its crucial role in amino acid transport and metabolism, the involvement of L-type amino acid transporter 1 (LAT1) and the potential therapeutic role of its inhibitor, JPH203, in fibrotic diseases remain unexplored. Considering the paucity of research on amino acid-mediated mTORC1 activation in PF, our study endeavors to elucidate the protective effects of JPH203 against PF and explore the involvement of amino acid-mediated mTORC1 signaling in this context. METHODS: We established the transforming growth factor beta 1 (TGF-ß1) induced MMT model in primary human mesothelial cells and the peritoneal dialysis fluid (PDF) induced PF model in mice. The therapeutic effects of JPH203 on PF were then examined on these two models by real-time quantitative polymerase chain reaction, western blotting, immunofluorescence staining, Masson's trichrome staining, H&E staining, picro-sirius red staining, and immunohistochemistry. The involvement of amino acid-mediated mTORC1 signaling was screened by RNA sequencing and further verified by western blotting in vitro. RESULTS: LAT1 was significantly upregulated and JPH203 markedly attenuated fibrotic phenotype both in vitro and in vivo. RNA-seq unveiled a significant enrichment of mTOR signaling pathway in response to JPH203 treatment. Western blotting results indicated that JPH203 alleviates PF by inhibiting amino acid-mediated mTORC1 signaling, which differs from the direct inhibition observed with rapamycin. CONCLUSION: JPH203 alleviates PF by inhibiting amino acid-mediated mTORC1 signaling.

The homeostasis of ions and reactive oxygen species in root and shoot play crucial roles in the tolerance of alfalfa to salt alkali stress.

High pH saline-alkali stress, mainly NaHCO3, limited the development of animal husbandry in Songnen Plain. Ion imbalance and reactive oxygen species (ROS) metabolism disorder caused by saline-alkali stress inhibited plant growth. In this study, we compared the differences in ion absorption, transport and ROS metabolism between saline-tolerant alfalfa (ZD) and saline-sensitive alfalfa (ZM) under NaHCO3 stress using physiology and transcripomics techniques. WGCNA analysis identified key genes associated with NaHCO3 stress-induced changes. NaHCO3 stress inhibited the absorption of K+ and Mg2+, but activated Ca2+ signal. Furthermore, ZD maintained higher K+, Mg2+ and Ca2+ contents and the K+/Na+ ratio than ZM, this is mainly related to the higher expression of proteins or channel-encoding genes involved in ion absorption and transport in ZD. Antioxidant enzyme systems can be activated in response to NaHCO3 stress. Peroxidase (EC 1.11.1.6), catalase (EC 1.11.1.7) and glutathione transferase (EC 2.5.1.18) activities were higher in ZD than ZM, and most genes encoding the relevant enzymes also demonstrated a stronger up-regulation trend in ZD. Although NaHCO3 stress inhibited Trx-Prx pathway, ZD related enzymes and their genes were also inhibited less than ZM. WGCNA results identified many genes involved in ion absorption, transport and antioxidant systems that play an important role in NaHCO3 stress adaptation. Collectively, ZD has the stronger ion homeostasis regulation and ROS scavenging ability, so it's more resistant to NaHCO3. The results provide theoretical guidance for further understanding of the molecular mechanism of NaHCO3 resistance and provide potential genes for research to improve saline-alkali tolerance in alfalfa.

Dissecting the Single-Cell Diversity and Heterogeneity Underlying Cervical Precancerous Lesions and Cancer Tissues.

The underlying cellular diversity and heterogeneity from cervix precancerous lesions to cervical squamous cell carcinoma (CSCC) is investigated. Four single-cell datasets including normal tissues, normal adjacent tissues, precancerous lesions, and cervical tumors were integrated to perform disease stage analysis. Single-cell compositional data analysis (scCODA) was utilized to reveal the compositional changes of each cell type. Differentially expressed genes (DEGs) among cell types were annotated using BioCarta. An assay for transposase-accessible chromatin sequencing (ATAC-seq) analysis was performed to correlate epigenetic alterations with gene expression profiles. Lastly, a logistic regression model was used to assess the similarity between the original and new cohort data (HRA001742). After global annotation, seven distinct cell types were categorized. Eight consensus-upregulated DEGs were identified in B cells among different disease statuses, which could be utilized to predict the overall survival of CSCC patients. Inferred copy number variation (CNV) analysis of epithelial cells guided disease progression classification. Trajectory and ATAC-seq integration analysis identified 95 key transcription factors (TF) and one immunohistochemistry (IHC) testified key-node TF (YY1) involved in epithelial cells from CSCC initiation to progression. The consistency of epithelial cell subpopulation markers was revealed with single-cell sequencing, bulk sequencing, and RT-qPCR detection. KRT8 and KRT15, markers of Epi6, showed progressively higher expression with disease progression as revealed by IHC detection. The logistic regression model testified the robustness of the resemblance of clusters among the various datasets utilized in this study. Valuable insights into CSCC cellular diversity and heterogeneity provide a foundation for future targeted therapy.

[Bipolar Action of Inhibitor of Vasculogenic Mimicry on Gene Expression in Melanoma Cells].

Multiple exogenous or endogenous factors alter gene expression patterns by different mechanisms that are poorly understood. We used RNA-Seq analysis in order to study changes in gene expression in melanoma cells that are capable of vasculogenic mimicry that is inhibited upon the action of an inhibitor of vasculogenic mimicry. Here, we show that the drug induces a strong upregulation of 50 genes that control the cell cycle and microtubule cytoskeleton coupled with a strong downregulation of 50 genes that control different cellular metabolic processes. We found that both groups of genes are simultaneously regulated by multiple sets of transcription factors. We conclude that one way for coordinated regulation of large groups of genes is regulation simultaneously by multiple transcription factors.

Integrated Single-cell RNA-seq and Bulk RNA-seq Identify Diagnostic Biomarkers for Postmenopausal Osteoporosis.

AIM: We aimed to explore diagnostic biomarkers of postmenopausal osteoporosis (PMOP). BACKGROUND: PMOP brings enormous physical and economic burden to elderly women. OBJECTIVES: This study aims to screen new biomarkers for osteoporosis, providing insights for early diagnosis and therapeutic targets of osteoporosis. METHODS: Weighted gene co-expression network analysis (WGCNA) was applied to identify osteoporosis-related hub genes. Single-cell transcriptomic atlas of osteoporosis was depicted and the heterogeneity of monocytes was analyzed, based on which the biomarkers for osteoporosis were screened. Gene set enrichment analysis (GSEA) was conducted on the biomarkers. The diagnostic model (nomogram) was established and evaluated based on the expression levels of biomarkers. Additionally, the transcription factor (TF) regulatory network was constructed to predict the potential TF and targeted miRNA of biomarkers. The drugs with significant correlation with biomarkers were identified by Spearman correlation analysis. RESULTS: We obtained 30 osteoporosis-associated hub genes. 9 cell types were identified, and the monocytes were subdivided to 4 subtypes. Three biomarkers, DHX29, LSM5, and UBE2V2, were screened. DHX29 and UBE2V2 were highly expressed in non-classical monocytes, while LSM5 exhibited the highest expression in other monocytes, followed by non-classical monocytes. GSEA indicated that osteoporosis may be correlated with vascular calcification and the biomarkers may be involved in the formation of immune cells. Then, nomogram was constructed and exhibited good robustness. In addition, MYC and SETDB1 were the shared IF in three biomarkers, which may play critical regulatory roles in the progression of osteoporosis. Moreover, 41, 49, and 68 drugs appeared significant correlations with DHX29, LSM5, and UBE2V2, respectively. CONCLUSION: This study provided a basis for early diagnosis and targeted treatment of osteoporosis.

Qianggan Ruanjian Pill ameliorates liver fibrosis through regulation of the TGF-ß1/Smad and PI3K/AKT signalling pathways.

ETHNOPHARMACOLOGICAL RELEVANCE: Liver fibrosis is a critical pathological process in the progression of chronic liver injury, ultimately resulting in cirrhosis, for which currently available therapeutic interventions remain inadequate. Among these, the Qianggan Ruanjian Pill (QGRJP) has emerged as a clinically experienced formula with notable therapeutic efficacy against liver fibrosis. However, the precise underlying mechanisms require further investigation. AIM OF THE STUDY: In this study, we investigated the key pathways and target genes of QGRJP that attenuate liver fibrosis and elucidated the underlying mechanisms. MATERIALS AND METHODS: High-performance liquid chromatography-mass spectrometry (HPLC-MS) was used to identify the major components of the QGRJP. Mouse models of liver fibrosis were established by injecting olive oil containing 25% carbon tetrachloride (CCl4), which was administered at different doses of QGRJP by gavage. Liver damage and function were assessed using serum biochemical detection, ultrasound imaging, and histopathological examination. The anti-fibrosis effect was assessed using immunohistochemistry, western blotting, and quantitative real-time PCR (qRT-PCR). The in vivo safety of the QGRJP was evaluated using weight monitoring and biopsy. Potential anti-liver fibrosis signalling pathways and key targets of QGRJP were identified using RNA-seq analysis and network pharmacology. The predicted targets and pathways were validated using in vitro and in vivo experiments. RESULTS: QGRJP significantly ameliorated CCl4-induced liver fibrosis, and its mechanism was correlated with the inhibition of hepatic stellate cell (HSC) activation and the inflammatory response via inhibition of the TGF-ß1/Smad and PI3K/AKT pathways, leading to a significant reduction in the expression of collagen and other fibrosis-related proteins. Additionally, no obvious toxic side effects were observed in the major organs of the mice or in activated HSCs (aHSCs). CONCLUSION: This study demonstrated that QGRJP mitigated liver injury, inflammation, and fibrosis by inhibiting the TGF-ß1/Smad and PI3K/AKT signalling pathways.

Transcriptomic analyses in the gametophytes of the apomictic fern Dryopteris affinis.

MAIN CONCLUSION: A novel genomic map of the apogamous gametophyte of the fern Dryopteris affinis unlocks oldest hindrance with this complex plant group, to gain insight into evo-devo approaches. The gametophyte of the fern Dryopteris affinis ssp. affinis represents a good model to explore the molecular basis of vegetative and reproductive development, as well as stress responses. Specifically, this fern reproduces asexually by apogamy, a peculiar case of apomixis whereby a sporophyte forms directly from a gametophytic cell without fertilization. Using RNA-sequencing approach, we have previously annotated more than 6000 transcripts. Here, we selected 100 of the inferred proteins homolog to those of Arabidopsis thaliana, which were particularly interesting for a detailed study of their potential functions, protein-protein interactions, and distance trees. As expected, a plethora of proteins associated with gametogenesis and embryogenesis in angiosperms, such as FERONIA (FER) and CHROMATING REMODELING 11 (CHR11) were identified, and more than a dozen candidates potentially involved in apomixis, such as ARGONAUTE family (AGO4, AGO9, and AGO 10), BABY BOOM (BBM), FASCIATED STEM4 (FAS4), FERTILIZATION-INDEPENDENT ENDOSPERM (FIE), and MATERNAL EFFECT EMBRYO ARREST29 (MEE29). In addition, proteins involved in the response to biotic and abiotic stresses were widely represented, as shown by the enrichment of heat-shock proteins. Using the String platform, the interactome revealed that most of the protein-protein interactions were predicted based on experimental, database, and text mining datasets, with MULTICOPY SUPPRESSOR OF IRA4 (MSI4) showing the highest number of interactions: 16. Lastly, some proteins were studied through distance trees by comparing alignments with respect to more distantly or closely related plant groups. This analysis identified DCL4 as the most distant protein to the predicted common ancestor. New genomic information in relation to gametophyte development, including apomictic reproduction, could expand our current vision of evo-devo approaches.

Elucidation of the pluripotent potential of bovine embryonic lineages facilitates the establishment of formative stem cell lines.

The establishment of epiblast-derived pluripotent stem cells (PSCs) from cattle, which are important domestic animals that provide humans with milk and meat while also serving as bioreactors for producing valuable proteins, poses a challenge due to the unclear molecular signaling required for embryonic epiblast development and maintenance of PSC self-renewal. Here, we selected six key stages of bovine embryo development (E5, E6, E7, E10, E12, and E14) to track changes in pluripotency and the dependence on signaling pathways via modified single-cell transcription sequencing technology. The remarkable similarity of the gene expression patterns between cattle and pigs during embryonic lineage development contributed to the successful establishment of bovine epiblast stem cells (bEpiSCs) using 3i/LAF (WNTi, GSK3ßi, SRCi, LIF, Activin A, and FGF2) culture system. The generated bEpiSCs exhibited consistent expression patterns of formative epiblast pluripotency genes and maintained clonal morphology, normal karyotypes, and proliferative capacity for more than 112 passages. Moreover, these cells exhibited high-efficiency teratoma formation as well as the ability to differentiate into various cell lineages. The potential of bEpiSCs for myogenic differentiation, primordial germ cell like cells (PGCLCs) induction, and as donor cells for cell nuclear transfer was also assessed, indicating their promise in advancing cell-cultured meat production, gene editing, and animal breeding.

Profiling genetically driven alternative splicing across the Indonesian archipelago.

One of the regulatory mechanisms influencing the functional capacity of genes is alternative splicing (AS). Previous studies exploring the splicing landscape of human tissues have shown that AS has contributed to human biology, especially in disease progression and the immune response. Nonetheless, this phenomenon remains poorly characterized across human populations, and it is unclear how genetic and environmental variation contribute to AS. Here, we examine a set of 115 Indonesian samples from three traditional island populations spanning the genetic ancestry cline that characterizes Island Southeast Asia. We conduct a global AS analysis between islands to ascertain the degree of functionally significant AS events and their consequences. Using an event-based statistical model, we detected over 1,500 significant differential AS events across all comparisons. Additionally, we identify over 6,000 genetic variants associated with changes in splicing (splicing quantitative trait loci [sQTLs]), some of which are driven by Papuan-like genetic ancestry, and only show partial overlap with other publicly available sQTL datasets derived from other populations. Computational predictions of RNA binding activity reveal that a fraction of these sQTLs directly modulate the binding propensity of proteins involved in the splicing regulation of immune genes. Overall, these results contribute toward elucidating the role of genetic variation in shaping gene regulation in one of the most diverse regions in the world.

Alternative splicing dysregulation across tissue and therapeutic approaches in a mouse model of myotonic dystrophy type 1.

Myotonic dystrophy type 1 (DM1), the leading cause of adult-onset muscular dystrophy, is caused by a CTG repeat expansion. Expression of the repeat causes widespread alternative splicing (AS) defects and downstream pathogenesis, including significant skeletal muscle impacts. The HSA LR mouse model plays a significant role in therapeutic development. This mouse model features a transgene composed of approximately 220 interrupted CTG repeats, which results in skeletal muscle pathology that mirrors DM1. To better understand this model and the growing number of therapeutic approaches developed with it, we performed a meta-analysis of publicly available RNA sequencing data for AS changes across three widely examined skeletal muscles: quadriceps, gastrocnemius, and tibialis anterior. Our analysis demonstrated that transgene expression correlated with the extent of splicing dysregulation across these muscles from gastrocnemius (highest), quadriceps (medium), to tibialis anterior (lowest). We identified 95 splicing events consistently dysregulated across all examined datasets. Comparison of splicing rescue across seven therapeutic approaches showed a range of rescue across the 95 splicing events from the three muscle groups. This analysis contributes to our understanding of the HSA LR model and the growing number of therapeutic approaches currently in preclinical development for DM1.