Integration Of Transcriptomics Research Articles

Spatially resolved multi-omics unravels region-specific responses, microenvironment remodeling and metabolic reprogramming in aristolochic acid nephropathy

<p>Aristolochic acid nephropathy (AAN), primarily caused by overexposure to aristolochic acid I (AAI), is characterized by acute renal injury, interstitial nephritis, and metabolic dysfunction. Previous studies have revealed the cell-specific responses to AAI and its role in inducing metabolic dysfunction. However, the lack of structural information in these datasets hinders our full understanding of the spatially specific pathological mechanisms of AAN. To address this limitation, we propose an integration of spatial transcriptomics with spatial metabolomics methods to establish a spatial multi-omics analysis, which allows for deciphering region-specific responses, microenvironmental remodeling, and metabolic reprogramming <i>in situ</i> in AAN. The pathological differences between renal regions indicate that AAI-induced renal injury exhibits spatial heterogeneity. With prolonged AAI treatment, we observed an increased proportion and co-localization of the injured proximal tubule (PT-inj) and immune cells in the cortex region, accompanied by intercellular crosstalk involving the MHC-I and CCL pathways. In addition, we identified a divergent cellular response along nephron segments, with up-regulation of multiple renal stress markers and pathways after AAI treatment. Regional heterogeneity of metabolic activities was also observed, with PT-inj cells exhibiting dysregulation of carbohydrate, lipid, and amino acid metabolic pathways, as well as increased purine and pyrimidine metabolism after AAI treatment. These findings provide a more comprehensive understanding of the cellular and molecular mechanisms of AAN in a spatial context, and suggest potential intervention pathways to alleviate the global burden of AAN.</p>

Transcriptomic Insight and Structural Integration: Repositioning FDA-Approved Methotrexate Derivative for Precision Therapy in Lung Cancer through Drug-Drug Similarity Analysis and Cavity-Guided Blind Docking

Transcriptomic Insight and Structural Integration: Repositioning FDA-Approved Methotrexate Derivative for Precision Therapy in Lung Cancer through Drug-Drug Similarity Analysis and Cavity-Guided Blind Docking

Metabolome and transcriptome integration reveals cerebral cortical metabolic profiles in rats with subarachnoid hemorrhage.

Subarachnoid hemorrhage (SAH) is a severe subtype of hemorrhagic stroke. The molecular mechanisms of its secondary brain damage remain obscure. To investigate the alterations in gene and metabolite levels following SAH, we construct the transcriptome and metabolome profiles of the rat cerebral cortex post-SAH using whole transcriptome sequencing and untargeted metabolomics assays. Transcriptomic analysis indicated that there were 982 differentially expressed genes (DEGs) and 540 differentially expressed metabolites (DEMs) between the sham group and SAH 1d, and 292 DEGs and 254 DEMs between SAH 1d and SAH 7d. Most notably, DEGs were predominantly involved in the activation of immune and inflammatory pathways, particularly the Complement and coagulation cascades, TNF signaling pathway, and NOD-like receptor signaling pathway. Metabolic analysis revealed that the metabolic pathways of Arginine and proline, Arachidonic acid, Folate biosynthesis, Pyrimidine, and Cysteine and methionine were remarkably affected after SAH. Metabolites of the above pathways are closely associated not only with immune inflammation but also with oxidative stress, endothelial cell damage, and blood-brain barrier disruption. This study provides new insights into the underlying pathologic mechanisms of secondary brain injury after SAH and further characterization of these aberrant signals could enable their application as potential therapeutic targets for SAH.

Exploring the Future of Plant Breeding: Advancements and Challenges

This review paper delves into the future of plant breeding by examining the advancements and challenges in the field. The introduction provides an overview of the historical evolution of plant breeding and highlights its relevance in addressing contemporary global challenges such as food security and climate change. The subsequent section explores the transition from conventional to molecular breeding techniques, showcasing the latest advancements in marker-assisted selection, genomic selection, and gene editing. Moreover, the review elucidates the significance of breeding stress-tolerant and adaptable crops to combat the effects of climate change and other environmental stressors. The integration of omics technologies, including genomics, transcriptomics, and proteomics, in plant breeding is discussed in detail to underscore their role in accelerating breeding progress. Finally, the paper addresses the challenges and ethical considerations associated with the future of plant breeding, including the adoption of genetically modified organisms and the need for robust regulatory frameworks. Overall, this review sheds light on the promising prospects and potential pitfalls in the domain of plant breeding, emphasizing the importance of sustainable and ethical practices.

Uncovering intestinal macrophages through the integration of single-cell and spatial transcriptomics.

Uncovering intestinal macrophages through the integration of single-cell and spatial transcriptomics.

COMPARATIVE TRANSCRIPTOMIC OF LONGEVITY

Abstract Transcriptome analysis provides a nuanced view into the changes that occur in cells and tissues. Transcriptome changes rapidly and reproducibly in response to physiological influences and environmental insults. Recent years have seen an exponential increase in transcriptome data at bulk, single cell and spatial resolution that allows insights into the mechanisms and regulatory pathways of aging and longevity. In this session Drs. Gorbunova (University of Rochester) and Gladyshev (Harvard Medical School) will discuss comparative transcriptomics of longevity across species with diverse lifespans that revealed unique signatures of longevity and the integration of transcriptome and proteome data. Dr. Gladyshev will discuss development of transcriptomic clocks of measuring biological aging. Dr. Artyomov will discuss single-cell resolution approaches to reveal aspects of immune aging in humans, and Dr. Palovics will present the use of transcriptomics to understand rejuvenating effects of heterochronic parabiosis.

Integration of transcriptome, metabolome and high-throughput amplicon sequencing to compare the performance of wild and cultivated psammosilene tunicoides to reveal the beneficial plant-microbe interactions for domestication

Psammosilene tunicoides is an herbal medicine with analgesic, anti-inflammatory and immunoregulatory properties, and it is listed as an International Union for the Conservation of Nature (IUCN) endangered species. The plants have been domesticated in some areas of Yunnan Province, China, for commercial and medical use. However, the performance of domesticated plants and the negative effects of domestication remain unclear. Multi-omics analyses were performed to compare the performance between wild P. tunicoides (WP) and cultivated P. tunicoides (CP). Transcriptomic and metabolomic data were generated from the roots, while microbiome data were obtained from the rhizospheres. The transcriptomic data showed that there were different patterns of gene expression between the WP and CP. The genes HMGS, HMGR, MPD and SQS, which are involved in the biosynthesis of triterpenoid saponins, were significantly more highly expressed in the WP than in the CP. The metabolomic analysis also found that significantly more triterpenoids were produced in the WP compared with the CP. The microbiome data showed that most of the plant growth-promoting rhizobacteria (PGPR), such as Burkholderia-Caballeronia-Paraburkholderia and others, were enriched in the WP type, while some pathogenic microorganisms were enriched in the CP type. A weighted gene co-expression network analysis revealed that the accumulation of triterpenoid saponins positively correlated with the modules of genes that primarily participated in the plant hormone signal transduction pathway and the PGPR in modules. This indicated that the triterpenoid saponins may function as signaling molecules to recruit the functional microbes. The regulatory “plant-microbe” network of microorganisms and the genes associated with triterpenes was detected in P. tunicoides. This suggests that the management of these interactions should be considered as a sustainable tool to enhance the performance of domesticated plants.

Integrating transcriptomics and biochemical analysis to understand the interactive mechanisms of the coexisting exposure of nanoplastics and erythromycin on Chlorella pyrenoidosa

Nanoplastics and antibiotics frequently co-exist in water polluted by algal blooms, but little information is available about interaction between substances. Erythromycin, as a representative of antibiotics, has been frequently detected in aquatic environments. This investigation attempted to reveal the interaction mechanism of nanoplastics and erythromycin on Chlorella pyrenoidosa. Results demonstrated that the joint toxicity of erythromycin and nanoplastics was dynamic and depended on nanoplastics concentration. Antagonistic effects of 1/2 or 1 EC50 erythromycin and nanoplastic concentration (10 mg/L) on the growth of C. pyrenoidosa was observed. The joint toxicity of 1/2 or 1 EC50 erythromycin and nanoplastic concentration (50 mg/L) was initially synergistic during 24–48 h and then turned to antagonistic during 72–96 h. Consequently, antagonistic effect was the endpoint for joint toxicity. Integration of transcriptomics and physiological biochemical analysis indicated that the co-existence of nanoplastics and erythromycin affected the signal transduction and molecular transport of algal cell membrane, induced intracellular oxidative stress, and hindered photosynthetic efficiency. Overall, this study provided a theoretical basis for evaluating the interactive mechanisms of nanoplastics and antibiotics.

Integration of transcriptome and DNA methylome analysis reveals the molecular mechanism of taproot yield heterosis in radish (Raphanus sativus L.)

Heterosis, a crucial biological phenomenon, plays a vital role in determining the yield and quality of plants. Radish, an important root vegetable crop, exhibits notable heterosis in terms of root yield and quality. Nevertheless, the specific molecular mechanism behind the formation of heterosis in radish remains unclear. Herein, transcriptome and DNA methylome analyses were performed on F1 hybrids and parental lines. Expression level dominance (ELD) genes and allele-specific expression (ASEG) genes together significantly contribute to heterosis, primarily through energy metabolism and plant hormone signal transduction pathway. Additionally, an increase in the average methylation level in the F1 hybrids was observed compared to the parental lines. Interestingly, a negative correlation was found between the methylation level of differentially expressed genes (DEGs) in gene body regions and their expression levels in NAU-LB and the F1 hybrids. Conversely, a contrasting trend was observed between NAU-YH and the F1 hybrids. Furthermore, when the parental lines and the F1 hybrids were treated with 5-azacytidine, the hybrids were more sensitive to methylation inhibitors than their parents. A significant decrease was observed in root weight and total sugar content in the F1 hybrids compared to the control. Immunolocalization results indicated a significant decrease in the auxin content of the F1 hybrid under 5-azacytidine treatment. Proliferating cell nuclear antigen immunolocalization also revealed significant inhibition of vascular cambium activity in both the hybrids and parental lines. Notably, the expression profiles of a few differentially methylated DEGs including RsSUS1, RsSUC2a, RsIAA7, and RsIAA18, were significantly increased in the root of hybrids compared to their parents, suggesting a potential role for DNA methylation in yield heterosis. Collectively, these findings would provide valuable insight into the molecular mechanism underlying taproot yield heterosis and have the potential to facilitate the genetic improvement of taproot yield and quality in radish breeding programs.

Understanding sex‐specific molecular mechanisms in preclinical and Alzheimer’s disease through brain proteomics and transcriptomics

AbstractBackgroundSex‐specific molecular mechanisms active during the transition from the preclinical stage to clinically evident Alzheimer’s disease (AD) pathobiology are not yet fully understood. In this study, we used large‐scale multi‐omics data integration of brain proteomics, brain transcriptomics, and genomics to study sex‐specific co‐expression changes related to the AD continuum.MethodsThe study included postmortem brain proteomics samples from the dorsolateral prefrontal cortex (DLPFC) of cases with AD dementia (N = 200, 55% female), cognitively unimpaired individuals with amyloid‐beta pathology (CU A+, N = 206, 70% female), and without (CU A‐, N = 110, 50% female) from the ROSMAP and Banner studies [Figure 1]. Additionally, RNAseq data was obtained from cases with AD dementia (N = 203, 70% female), CU A+ (N = 204, 63% female), and Cu A‐ (N = 125, 56% female) from ROSMAP. We performed co‐expression network analysis to identify functional sex‐specific molecular modules that differentially behave in AD different stages along the AD continuum (AD dementia vs. CU A‐, CU A+ vs. CU A‐). We assessed the preservation of these modules in the brain transcriptome. Additionally, brain protein quantitative trait loci (pQTLs) enrichment analysis was performed to characterize significant modules enriched for AD risk variants. Finally, we assessed the association of sex‐specific modules with AD traits.ResultsProteomic network analysis showed modules significantly associated with pathological traits differentially by sex [Figure 2]. For instance, a module related to cellular localization showed upregulation in AD and CU A+ compared with CU A‐ [Figure 3A]. Association with pathological traits showed a positive correlation with global pathology and a negative correlation with global cognition only in female [Figure 3B]. In males, two modules related to ubiquitin proteolysis were changed in AD dementia and CU A+. Brain transcriptome showed preservation of the cellular localization module in female [Figure 3C]. This module was enriched for AD pQTLs in the brain, including variants from SYN3, FLOT2 and PACSIN2, which are involved in processing of amyloid and vesicle trafficking [Figure 3D] ConclusionsThis multi‐omics system network analysis reveals changes of a cellular localization‐related module, specifically in the females AD brain proteome and transcriptome, which could be used as potential therapeutic targets.

Integration of single-cell transcriptomics and epigenetic analysis reveals enhancer-controlled TIMP1 as a regulator of ferroptosis in colorectal cancer.

Ferroptosis is an iron-dependent non-apoptotic programmed cell death. However, the regulatory mechanism of ferroptosis in colorectal cancer (CRC) is still unclear. The aim of this study was to investigate the role and mechanism of enhancer-controlled genes in ferroptosis in CRC. Dimensionality reduction and differentially expressed genes (DEGs) identification were conducted using Seurat algorithm based on single-cell RNA sequencing (scRNA-seq) data from the GSE200997 dataset. Ferroptosis-related pathway enrichment analysis was performed using the FerrDb V2 database. Enhancers were identified using HOMER algorithm based on H3K27ac ChIP-seq data from the GSE166254 dataset. Kaplan-Meier Plotter online tool was used to analyze prognosis and gene expression correlation. Transcription factors were predicted using the transcription factor affinity prediction web tool. The binding of enhancer to transcription factor and H3K27ac enrichment were detected by ChIP-qPCR. RSL3 was used to induce ferroptosis in CRC cells. Gene transcription was detected by qRT-PCR. Cell proliferation was detected by CCK8 assay. Nine cell clusters including T cells, natural killer cells, macrophages, mast cells, epithelial cells, fibroblasts, goblet cells, B cells and dendritic cells were identified in CRC and normal colonic tissue samples. Compared to normal colonic tissue-derived epithelial cells, 1075 DEGs were screened in CRC tissue-derived epithelial cells. Ferroptosis-related pathway enrichment suggested that DEGs were associated with the regulation of ferroptosis. DPEP1, ETV4, CEBPG, TIMP1, DUOX2 and LCN2 were identified as the significantly upregulated genes enriched in the "ferroptosis regulator" term, and their H3K27ac signals were significantly higher in CRC tissues than in normal colonic tissues. Of these, only the expression of TIMP1 predicted a poor prognosis of CRC patients. Transcription factor SPI1 drove TIMP1 transcription by binding to its enhancer. Overexpression of TIMP1 significantly promoted the resistance to ferroptosis induced by RSL3 in CRC cells, which was partially restored by SPI1 knockdown. Transcription of TIMP1 was driven by transcription factor SPI1 in combination with its enhancer, consequently promoting CRC cells against ferroptosis. The SPI1/TIMP1 axis confers ferroptosis resistance in CRC, and thus has the potential to be the molecular targets for CRC treatment.

Precise Single-Cell Transcriptomic Mapping of Leukemia Cell States Reveals Unconventional Lineage Priming in Acute Myeloid Leukemia

Initial disease classification within acute leukemia relies on identifying morphological and immunophenotypic features of hematopoietic differentiation retained by leukemic blasts. While existing approaches can classify leukemic cells into broad lineages, they lack precision in discerning between specific cell states, particularly at the level of immature blasts. Single-cell (sc) RNA-sequencing (RNA-seq) provides thousands of new markers to enable precise determination of leukemia cell state and provides an opportunity to refine our classification of acute leukemia. To extend our ability to identify leukemia cell states by scRNA-seq, we developed a comprehensive reference map of human bone marrow hematopoiesis. Specifically, we integrated three unsorted bone marrow datasets and three CD34+ hematopoietic stem and progenitor (HSPC) purified datasets to ensure balanced representation of early HSPCs and terminally differentiated immune cells. This culminated in a curated atlas of 263,159 high-quality sc transcriptomes, representing 55 cellular states spanning 45 healthy donors (Fig 1A). We validated our cell state annotations to ensure concordance between transcriptional states and functional populations through reference mapping of bulk and sc transcriptomes from purified HSPC subsets. For example, mapping of scRNA-seq profiles from Lin-CD34+38-45RA-90+49f+ long-term (LT) HSCs revealed 91% concordance between transcriptional HSC and functional LT-HSC. We next performed scRNA-seq profiling on 12 AML patient samples harbouring either myelodysplasia-related genetic features or classical alterations involving NPM1 or KMT2A. By mapping leukemia cells onto our reference atlas, we identified pronounced involvement of early erythroid-like blasts in a subset of AML samples. To further investigate unconventional lineage priming in AML, we processed and mapped scRNA-seq profiles from eleven studies comprising 166 additional AML samples and 9 mixed phenotype acute leukemia (MPAL) samples (Fig 1B). After quality control and exclusion of mature lymphoid cells, we performed composition analysis utilizing 600,570 leukemia cells mapped to 38 cell states to identify patterns of variation among leukemia cell states. Immature leukemia cells map to a range of cellular states spanning HSC/MPP-like, LMPP-like, MLP-like, GMP-like, MEP-like, and EarlyEry-like, among others. Notably, we identified a subset of AMLs with high MLP-like enrichment that co-cluster with MPALs as well as a subset with high EarlyEry-like involvement that co-cluster with acute erythroid leukemias (AEL), thus highlighting the biological continuum between these diseases. We next identified marker genes from each leukemia cell state and trained sparse regression models to estimate their relative abundance within bulk RNA-seq cohorts. Through bulk analysis, we confirmed that MPAL is highly enriched for MLP-like cells compared to AML (p=2.5e-12) and that M6 AELs are highly enriched for EarlyEry-like cells compared to M0-M5 AMLs (p=0.00067). Among 864 AML patients, we found that high MLP-like abundance was associated with NUP98-NSD1 fusions (p=0.0011) and RUNX1 mutations (p=8.0e-10) while high EarlyEry-like abundance was associated with Complex Cytogenetics (p=8e-15) and TP53 mutations (p=2.3e-25). Cellular states of immature leukemic cells captured inter-patient heterogeneity within 136 AEL samples, wherein high EarlyEry-like abundance was associated with TP53 mutations (p=3.6e-9) and Poor cytogenetic risk (p=1.1e-9) while high GMP-like abundance was associated with KMT2A alterations (p=0.00046) and Good/Intermediate risk (p=0.00032). Finally, through integration of sc transcriptomics and targeted DNA profiling, we found examples of genetic subclones impacting the cellular hierarchies of individual patients through induction of early differentiation blocks, skewing of lineage output from myeloid to erythroid, or potentiation of transcriptional self-renewal programs within mature myeloid cells. Together, our high-resolution mapping approach highlights the cellular state continuum between acute leukemias and enumerates the impact of genetic drivers on leukemia cell hierarchies. Precise definitions of cellular states, coupled with the presence or absence of genetic alterations, may help to refine future disease classification, prognostication, and therapy development.

Integration of Metabolomes and Transcriptomes Provides Insights into Morphogenesis and Maturation in Morchella sextelata.

True morels (Morchella, Pezizales) are a popular edible and medicinal fungus with great nutritional and economic value. The dynamics and regulatory mechanisms during the morphogenesis and maturation of morels are poorly understood. In this study, the metabolomes and transcriptomes of the mycelium (MY), primordium differentiation (PR), young fruiting body (YFB), and mature fruiting body (MFB) were comprehensively analyzed to reveal the mechanism of the morphogenesis and maturation of Morchella sextelata. A total of 748 differentially expressed metabolites (DEMs) and 5342 differentially expressed genes (DEGs) were detected, mainly enriched in the carbohydrate, amino acid, and lipid metabolism pathways, with the transition from the mycelium to the primordium being the most drastic stage at both the metabolic and transcriptional levels. The integrated metabolomics and transcriptomics highlighted significant correlations between the DEMs and DEGs, and specific amino acid and nucleotide metabolic pathways were significantly co-enriched, which may play key roles in morphological development and ascocarp maturation. A conceptual model of transcriptional and metabolic regulation was proposed during morphogenesis and maturation in M. sextelata for the first time, in which environmental factors activate the regulation of transcription factors, which then promote metabolic and transcriptional regulation from vegetative to reproductive growth. These results provide insights into the metabolic dynamics and transcriptional regulation during the morphogenesis and maturation of morels and valuable resources for future breeding enhancement and sustainable artificial cultivation.

Genomic and Transcriptomic Approaches to Developing Abiotic Stress-Resilient Crops

In the realm of agriculture, a pressing concern remains the abiotic stresses, such as temperature fluctuation, drought, soil salinity, and heavy metal contamination. These adverse growth conditions hamper crop yields and global food security. In this review, we present a comprehensive examination of the recent advancements in utilizing genomics and transcriptomics, tools to enhance crop resilience against these stress factors. Genomics aids in the identification of genes responsive to stress, unravels regulatory networks, and pinpoints genetic variations linked to stress tolerance. Concurrently, transcriptomics sheds light on the intricate dynamics of gene expression during stress conditions, unearthing novel stress-responsive genes and signaling pathways. This wealth of knowledge shapes the development of stress-tolerant crop varieties, achieved through conventional breeding programs and state-of-the-art genetic engineering and gene editing techniques like CRISPR-Cas9. Moreover, the integration of diverse omics data and functional genomics tools empowers precise manipulation of crop genomes to fortify their stress resilience. In summary, the integration of genomics and transcriptomics holds substantial promise in elucidating the molecular mechanisms behind crop stress tolerance, offering a path towards sustainable agriculture and safeguarding food security amidst shifting environmental challenges.

Transcriptomic and Metabolomic Analyses Reveal the Importance of Lipid Metabolism and Photosynthesis Regulation in High Salinity Tolerance in Barley (Hordeum vulgare L.) Leaves Derived from Mutagenesis Combined with Microspore Culture

Barley is the most salt-tolerant cereal crop. However, little attention has been paid to the salt-tolerant doubled haploids of barley derived from mutagenesis combined with isolated microspore culture. In the present study, barley doubled haploid (DH) line 20, which was produced by mutagenesis combined with isolated microspore culture, showed stably and heritably better salt tolerance than the wild type H30 in terms of fresh shoot weight, dry shoot weight, K+/Na+ ratio and photosynthetic characteristics. Transcriptome and metabolome analyses were performed to compare the changes in gene expression and metabolites between DH20 and H30. A total of 462 differentially expressed genes (DEGs) and 152 differentially accumulated metabolites (DAMs) were identified in DH20 compared to H30 under salt stress. Among the DAMs, fatty acids were the most accumulated in DH20 under salt stress. The integration of transcriptome and metabolome analyses revealed that nine key biomarkers, including two metabolites and seven genes, could distinguish DH20 and H30 when exposed to high salt. The pathways of linoleic acid metabolism, alpha-linolenic acid metabolism, glycerolipid metabolism, photosynthesis, and alanine, aspartate and glutamate metabolism were significantly enriched in DH20 with DEGs and DAMs in response to salt stress. These results suggest that DH20 may enhance resilience by promoting lipid metabolism, maintaining energy metabolism and decreasing amino acids metabolism. The study provided novel insights for the rapid generation of homozygous mutant plants by mutagenesis combined with microspore culture technology and also identified candidate genes and metabolites that may enable the mutant plants to cope with salt stress.

Integration of Transcriptomics and Proteomics Analysis Reveals the Molecular Mechanism of Eriocheir sinensis Gills Exposed to Heat Stress.

Heat stress is an increasingly concerning topic under global warming. Heat stress can induce organisms to produce excess reactive oxygen species, which will lead to cell damage and destroy the antioxidant defense of aquatic animals. Chinese mitten crab, Eriocheir sinensis, is sensitive to the change in water temperature, and parent crabs are more vulnerable during the breeding stage. In the present study, the multi-omics responses of parent E. sinensis gills to heat stress (24 h) were determined via transcriptome and proteome. The integrative analysis revealed that heat shock protein 70 (HSP70) and glutathione s-transferase (GST) were significantly up-regulated at gene and protein levels after heat stress, indicating that HSP70 and the antioxidant system participated in the regulatory mechanism of heat stress to resist oxidative damage. Moreover, the "Relaxin signaling pathway" was also activated at gene and protein levels under 30 °C stress, which implied that relaxin may be essential and responsible for reducing the oxidative damage of gills caused by extreme heat stress. These findings provided an understanding of the regulation mechanism in E. sinensis under heat stress at gene and protein levels. The mining of key functional genes, proteins, and pathways can also provide a basis for the cultivation of new varieties resistant to oxidative stress.

Transcriptomic Integration Analyses Uncover Common Bisphenol A Effects Across Species and Tissues Primarily Mediated by Disruption of JUN/FOS, EGFR, ER, PPARG, and P53 Pathways.

Bisphenol A (BPA) is a common endocrine disruptor widely used in the production of electronic, sports, and medical equipment, as well as consumer products like milk bottles, dental sealants, and thermal paper. Despite its widespread use, current assessments of BPA exposure risks remain limited due to the lack of comprehensive cross-species comparative analyses. To address this gap, we conducted a study aimed at identifying genes and fundamental molecular processes consistently affected by BPA in various species and tissues, employing an effective data integration method and bioinformatic analyses. Our findings revealed that exposure to BPA led to significant changes in processes like lipid metabolism, proliferation, and apoptosis in the tissues/cells of mammals, fish, and nematodes. These processes were found to be commonly affected in adipose, liver, mammary, uterus, testes, and ovary tissues. Additionally, through an in-depth analysis of signaling pathways influenced by BPA in different species and tissues, we observed that the JUN/FOS, EGFR, ER, PPARG, and P53 pathways, along with their downstream key transcription factors and kinases, were all impacted by BPA. Our study provides compelling evidence that BPA indeed induces similar toxic effects across different species and tissues. Furthermore, our investigation sheds light on the underlying molecular mechanisms responsible for these toxic effects. By uncovering these mechanisms, we gain valuable insights into the potential health implications associated with BPA exposure, highlighting the importance of comprehensive assessments and awareness of this widespread endocrine disruptor.

Transcriptome and lipidome integration unveils mechanisms of fatty liver formation in Shitou geese

Geese evolved from migratory birds, and when they consume excessive high-energy feed, glucose is converted into triglycerides. A large amount of triglyceride deposition can induce incomplete oxidation of fatty acids, leading to lipid accumulation in the liver and the subsequent formation of fatty liver. In the Chaoshan region of Guangdong, China, Shitou geese develop a unique form of fatty liver through 24 h overfeeding of brown rice. To investigate the mechanisms underlying the formation of fatty liver in Shitou geese, we collected liver samples from normally fed and overfed geese. The results showed that the liver size in the treatment group was significantly larger, weighing 3.5 times more than that in the control group. Extensive infiltration of lipid droplets was observed in the liver upon staining of tissue sections. Biochemical analysis revealed that compared to the control group, the treatment group showed significantly elevated levels of total cholesterol (T-CHO), triglycerides (TG), and glycogen in the liver. However, no significant differences were observed in the levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST), which are common indicators of liver damage. Furthermore, we performed a combined transcriptomic and lipidomic analysis of the liver samples and identified 1,510 differentially expressed genes (DEGs) and 1,559 significantly differentially abundant metabolites (SDMs). The enrichment analysis of the DEGs revealed their enrichment in metabolic pathways, cellular process-related signaling pathways, and specific lipid metabolism pathways. We also conducted KEGG enrichment analysis of the SDMs and compared them with the enriched signaling pathways obtained from the DEGs. In this study, we identified 3 key signaling pathways involved in the formation of fatty liver in Shitou geese, namely, the biosynthesis of unsaturated fatty acids, glycerol lipid metabolism, and glycerophospholipid metabolism. In these pathways, genes such as glycerol-3-phosphate acyltransferase, mitochondrial (GPAM), 1-acylglycerol-3-phosphate O-acyltransferase 2 (AGPAT2), diacylglycerol O-acyltransferase 2 (DGAT2), lipase, endothelial (LIPG), lipoprotein lipase (LPL), phospholipase D family member 4 (PLD4), and phospholipase A2 group IVF (PLA2G4F) may regulate the synthesis of metabolites, including triacylglycerol (TG), phosphatidate (PA), 1,2-diglyceride (DG), phosphatidylethanolamine (PE), and phosphatidylcholine (PC). These genes and metabolites may play a predominant role in the development of fatty liver, ultimately promoting the accumulation of TG in the liver and leading to the progression of fatty liver.

Integration of Metabolomics and Transcriptomics to Explore Dynamic Alterations in Fruit Color and Quality in 'Comte de Paris' Pineapples during Ripening Processes.

Pineapple color yellowing and quality promotion gradually manifest as pineapple fruit ripening progresses. To understand the molecular mechanism underlying yellowing in pineapples during ripening, coupled with alterations in fruit quality, comprehensive metabolome and transcriptome investigations were carried out. These investigations were conducted using pulp samples collected at three distinct stages of maturity: young fruit (YF), mature fruit (MF), and fully mature fruit (FMF). This study revealed a noteworthy increase in the levels of total phenols and flavones, coupled with a concurrent decline in lignin and total acid contents as the fruit transitioned from YF to FMF. Furthermore, the analysis yielded 167 differentially accumulated metabolites (DAMs) and 2194 differentially expressed genes (DEGs). Integration analysis based on DAMs and DEGs revealed that the biosynthesis of plant secondary metabolites, particularly the flavonol, flavonoid, and phenypropanoid pathways, plays a pivotal role in fruit yellowing. Additionally, RNA-seq analysis showed that structural genes, such as FLS, FNS, F3H, DFR, ANR, and GST, in the flavonoid biosynthetic pathway were upregulated, whereas the COMT, CCR, and CAD genes involved in lignin metabolism were downregulated as fruit ripening progressed. APX as well as PPO, and ACO genes related to the organic acid accumulations were upregulated and downregulated, respectively. Importantly, a comprehensive regulatory network encompassing genes that contribute to the metabolism of flavones, flavonols, lignin, and organic acids was proposed. This network sheds light on the intricate processes that underlie fruit yellowing and quality alterations. These findings enhance our understanding of the regulatory pathways governing pineapple ripening and offer valuable scientific insight into the molecular breeding of pineapples.

SCInter: a comprehensive single-cell transcriptome integration database for human and mouse

Single-cell RNA sequencing (scRNA-seq), which profiles gene expression at the cellular level, has effectively explored cell heterogeneity and reconstructed developmental trajectories. With the increasing research on diseases and biological processes, scRNA-seq datasets are accumulating rapidly, highlighting the urgent need for collecting and processing these data to support comprehensive and effective annotation and analysis. Here, we have developed a comprehensive Single-Cell transcriptome integration database for human and mouse (SCInter, https://bio.liclab.net/SCInter/index.php), which aims to provide a manually curated database that supports the provision of gene expression profiles across various cell types at the sample level. The current version of SCInter includes 115 integrated datasets and 1016 samples, covering nearly 150 tissues/cell lines. It contains 8016,646 cell markers in 457 identified cell types. SCInter enabled comprehensive analysis of cataloged single-cell data encompassing quality control (QC), clustering, cell markers, multi-method cell type automatic annotation, predicting cell differentiation trajectories and so on. At the same time, SCInter provided a user-friendly interface to query, browse, analyze and visualize each integrated dataset and single cell sample, along with comprehensive QC reports and processing results. It will facilitate the identification of cell type in different cell subpopulations and explore developmental trajectories, enhancing the study of cell heterogeneity in the fields of immunology and oncology.