RNA-seq Methods Research Articles

Lasy-Seq: A High-Throughput 3' RNA-Seq Method for Large-Scale Transcriptome Profiling in Rice.

Lasy-Seq (low-cost and easy RNA-seq) is a high-throughput library preparation method for 3' RNA-seq. Usage of oligo(dT) primers with unique index sequences allows simultaneous reverse transcription (RT) reaction and sample indexing. Therefore, each post-RT step, which was performed on a sample-by-sample basis in a conventional method, can be performed on a large number of samples together in a single tube. With the Lasy-Seq, the sequencing-ready library pool can be prepared from a few to several hundred samples in a few days.

Identification of Target Gene and Interacting Protein of Two LaSCL6 Alternative Splicing Variants Provides Novel Insights into Larch Somatic Embryogenesis.

Somatic embryogenesis is valuable for clonal propagation and genetic improvement, and it also serves as an ideal system for studying plant development mechanisms. In Larix kaempferi, microRNA171 and its target gene L. kaempferi SCARECROW-LIKE6 (LaSCL6), which has two alternative splicing variants, can regulate somatic embryogenesis; however, the underlying molecular mechanism is still unknown. In this study, we overexpressed these two LaSCL6 variants in Oryza sativa and Arabidopsis thaliana and then used the RNA-Seq method to screen genes from O. sativa and A. thaliana, whose expression patterns are related to those of LaSCL6 variants. The screened genes were then used to search L. kaempferi proteins to identify the candidate target genes of LaSCL6. After yeast one-hybrid and dual- luciferase transcriptional activity assays, cytochrome P450, family 89, subfamily A, polypeptide 5 (CYP89A5), and wall-associated receptor kinase-like 20 (WAKL20) were confirmed to be the target genes of LaSCL6-var1; in addition, WAKL20 and UDP-glycosyltransferase 85A3 (UGT85A3) were confirmed to be the target genes of LaSCL6-var2. Moreover, APETALA2-like protein 2, a transcription factor from the AP2/ERF family, was shown to interact with LaSCL6-var1 and LaSCL6-var2. Taken together, our results suggest a regulatory network of miR171-LaSCL6. The findings presented here not only provide novel insights into the regulation of the miR171-LaSCL6 module but also explain the mechanism underlying larch somatic embryogenesis and other biological processes.

A benchmark of RNA-seq data normalization methods for transcriptome mapping on human genome-scale metabolic networks

Genome-scale metabolic models (GEMs) cover the entire list of metabolic genes in an organism and associated reactions, in a tissue/condition non-specific manner. RNA-seq provides crucial information to make the GEMs condition-specific. Integrative Metabolic Analysis Tool (iMAT) and Integrative Network Inference for Tissues (INIT) are the two most popular algorithms to create condition-specific GEMs from human transcriptome data. The normalization method of choice for raw RNA-seq count data affects the model content produced by these algorithms and their predictive accuracy. However, a benchmark of the RNA-seq normalization methods on the performance of iMAT and INIT algorithms is missing in the literature. Another important phenomenon is covariates such as age and gender in a dataset, and they can affect the predictivity of analysis. In this study, we aimed to compare five different RNA-seq data normalization methods (TPM, FPKM, TMM, GeTMM, and RLE) and covariate adjusted versions of the normalized data by mapping them on a human GEM using the iMAT and INIT algorithms to generate personalized metabolic models. We used RNA-seq data for Alzheimer’s disease (AD) and lung adenocarcinoma (LUAD) patients. The results demonstrated that RNA-seq data normalized by the RLE, TMM, or GeTMM methods enabled the production of condition-specific metabolic models with considerably low variability in terms of the number of active reactions compared to the within-sample normalization methods (FPKM, TPM). Using these models, we could more accurately capture the disease-associated genes (average accuracy of ~0.80 for AD and ~0.67 for LUAD) for the RLE, TMM, and GeTMM normalization methods. An increase in the accuracies was observed for all the methods when covariate adjustment was applied. We found a similar accuracy trend when we compared the metabolites of perturbed reactions to metabolome data for AD. Together, our benchmark study shows that the between-sample RNA-seq normalization methods reduce false positive predictions at the expense of missing some true positive genes when mapped on GEMs.

Biochemical and Transcriptomic Analyses Reveal Key Salinity and Alkalinity Stress Response and Tolerance Pathways in Salix linearistipularis Inoculated with Trichoderma

Soil salinization and alkalinization are pervasive environmental issues that severely restrict plant growth and crop yield. Utilizing plant growth-promoting rhizobacteria (PGPR) is an effective strategy to enhance plant tolerance to saline–alkaline stress, though the regulatory mechanisms remain unclear. This study employed biochemical and RNA-Seq methods to uncover the critical growth-promoting effects of Trichoderma spp. on Salix linearistipularis under saline–alkaline stress. The results showed that, during saline–alkaline stress, inoculation with Trichoderma sp. M4 and M5 significantly increased the proline and soluble sugar contents in Salix linearistipularis, enhanced the activities of SOD, POD, CAT, and APX, and reduced lipid peroxidation levels, with M4 exhibiting more pronounced effects than M5. RNA-Seq analysis of revealed that 11,051 genes were upregulated after Trichoderma sp. M4 inoculation under stress conditions, with 3532 genes primarily involved in carbon metabolism, amino acid biosynthesis, and oxidative phosphorylation—processes that alleviate saline–alkaline stress. Additionally, 7519 genes were uniquely upregulated by M4 under stress, mainly enriched in secondary metabolite biosynthesis, amino acid metabolism, cyanamide metabolism, and phenylpropanoid biosynthesis. M4 mitigates saline–alkaline stress-induced damage in Salix linearistipularis seedlings by reducing oxidative damage, enhancing organic acid and amino acid metabolism, and activating phenylpropanoid biosynthesis pathways to eliminate harmful ROS. This enhances the seedlings’ tolerance to saline–alkaline stress, providing a basis for studying fungi–plant interactions under such conditions.

Characterization of Hibiscus Chlorotic Ringspot Virus-Derived vsiRNAs from Infected Hibiscus rosa-sinensis in China.

Lots of progress have been made about pathogen system of Hibiscus rosa-sinensis and hibiscus chlorotic ringspot virus (HCRSV), however, interactions between H. rosa-sinensis and HCRSV remain largely unknown. Hereon, firstly, HCRSV infection in H. rosa-sinensis from Zhangzhou city of China was confirmed by traditional electron microscopy, modern reverse transcription polymerase chain reaction and RNA-seq methods. Secondly, sequence feature analysis showed the full-length sequence of HCRSV-ZZ was 3,909 nucleotides (nt) in length and had a similar genomic structure with other carmovirus. It contains a 5' untranslated region (UTR), followed by seven open reading frames encoding for P28, P23, P81, P8, P9, P38, and P25, and the last a 3-terminal UTR. Thirdly, HCRSV- ZZ-derived vsiRNAs were identified and characterized for the first time from disease H. rosa-sinensis through sRNA-seq to reveal interactions between pathogen ant plant host. It was shown that the majority of HCRSV-ZZ-derived vsiRNAs were 21 nt, 22 nt, and 20 nt, with 21 nt being most abundant. The 5'-terminal nucleotide of HCRSV-ZZ vsiRNAs preferred U and C. HCRSV-ZZ vsiRNAs derived predominantly (72%) from the viral genome positive-strand RNA. The distribution of HCRSV-ZZ vsiRNAs along the viral genome is generally even, with some hot spots and cold spots forming in local regions. These hot spots and cold spots could be corresponded to the regions of stem loop secondary structures forming in HCRSV-ZZ genome by nucleotide paring. Taken together, our findings certify HCRSV infection in H. rosa-sinensis and provide an insight into interaction between HCRSV and H. rosa-sinensis and contribute to the prevention and treatment of this virus.

Machine learning-optimized targeted detection of alternative splicing.

RNA-sequencing (RNA-seq) is widely adopted for transcriptome analysis but has inherent biases which hinder the comprehensive detection and quantification of alternative splicing. To address this, we present an efficient targeted RNA-seq method that greatly enriches for splicing-informative junction-spanning reads. Local Splicing Variation sequencing (LSV-seq) utilizes multiplexed reverse transcription from highly scalable pools of primers anchored near splicing events of interest. Primers are designed using Optimal Prime, a novel machine learning algorithm trained on the performance of thousands of primer sequences. In experimental benchmarks, LSV-seq achieves high on-target capture rates and concordance with RNA-seq, while requiring significantly lower sequencing depth. Leveraging deep learning splicing code predictions, we used LSV-seq to target events with low coverage in GTEx RNA-seq data and newly discover hundreds of tissue-specific splicing events. Our results demonstrate the ability of LSV-seq to quantify splicing of events of interest at high-throughput and with exceptional sensitivity.

Garlic-derived Exosomes Alleviate Osteoarthritis Through Inhibiting the MAPK Signaling Pathway.

Osteoarthritis (OA) is the most common degenerative joint disease affecting millions of people worldwide. Garlic-derived exosomes (GDEs) are nanoparticles extracted from garlic that exhibit anti-inflammatory effects on other diseases, but the effect of GDEs on OA has not been elucidated. In this study, GDEs were extracted and characterized. Chondrocytes were treated with IL-1β and incubated with GDEs in vitro, and the expression of cartilage matrix components (collagen II and aggrecan) and matrix degrading enzymes (MMP3 and MMP9) was evaluated via Western blotting. Changes in the MAPK pathway was also examined using Western blotting. The transcriptomic changes associated with GDE intervention were evaluated using high-throughput RNA-seq method. In vivo, we used anterior cruciate ligament transection (ACLT) combined with destabilization of the medial meniscus (DMM) surgery to establish a mouse OA model, and GDEs was intraarticularly injected into the joint cavity. The therapeutic effect of GDE was evaluated by behavioral and histopathological analysis. The results showed that IL-1β treatment inhibited the expression of collagen II and aggrecan, and upregulated the expression of MMP3 and MMP9, while GDE intervention alleviated these effects. GDEs also inhibited the phosphorylation of ERK, JNK, and P38. In vivo, GDE alleviated the sensitivity to heat stimulation and altered walking gait in a mouse OA model. Histopathological analysis indicated that GDE intervention ameliorated joint destruction in the knee joint without obvious toxicity. The results proved that GDEs alleviated the progression of OA in vitro and in vivo, and may be a potential disease-modifying drug for OA.

Purity Independent Subtyping of Tumors (PurIST) Pancreatic Cancer Classifier: Analytic Validation of a 16-RNA Expression Signature Distinguishing Basal and Classical Subtypes

The two major molecular subtypes of pancreatic adenocarcinoma reportedly have differential response to FOLFIRINOX-based therapy. To promote rapid assignment of basal versus classical subtypes, an array-based single-sample classifier assay was developed and applied to 74 formalin-fixed, paraffin-embedded biopsy or resection specimens of known subtype based on transcriptomics. The Purity Independent Subtyping of Tumors (PurIST) algorithm assigns subtype based on relative expression of 16 RNAs counted by RNA sequencing (RNAseq) versus more practical array-based NanoString nCounter Elements XT technology. Subtype calls were largely concordant between RNAseq and array methods (72/74, 97% agreement). Compared with the lengthy RNAseq protocol, the array-based assay takes just 3 working days to analyze, permitting rapid reporting of tumor subtype. In conclusion, the PurIST pancreatic cancer classifier has robust performance to classify pancreatic adenocarcinoma into basal versus classical subtypes. Clinical validation studies are underway to evaluate outcome in patients whose standard-of-care chemotherapy regimen is selected on the basis of rapid subtype assignment (NCT04683315).

Single-cell total-RNA profiling unveils regulatory hubs of transcription factors

Recent development of RNA velocity uses master equations to establish the kinetics of the life cycle of RNAs from unspliced RNA to spliced RNA (i.e., mature RNA) to degradation. To feed this kinetic analysis, simultaneous measurement of unspliced RNA and spliced RNA in single cells is greatly desired. However, the majority of single-cell RNA-seq chemistry primarily captures mature RNA species to measure gene expressions. Here, we develop a one-step total-RNA chemistry-based single-cell RNA-seq method: snapTotal-seq. We benchmark this method with multiple single-cell RNA-seq assays in their performance in kinetic analysis of cell cycle by RNA velocity. Next, with LASSO regression between transcription factors, we identify the critical regulatory hubs mediating the cell cycle dynamics. We also apply snapTotal-seq to profile the oncogene-induced senescence and identify the key regulatory hubs governing the entry of senescence. Furthermore, from the comparative analysis of unspliced RNA and spliced RNA, we identify a significant portion of genes whose expression changes occur in spliced RNA but not to the same degree in unspliced RNA, indicating these gene expression changes are mainly controlled by post-transcriptional regulation. Overall, we demonstrate that snapTotal-seq can provide enriched information about gene regulation, especially during the transition between cell states.

An improved bacterial mRNA enrichment strategy in dual RNA sequencing to unveil the dynamics of plant-bacterial interactions

BackgroundDual RNA sequencing is a powerful tool that enables a comprehensive understanding of the molecular dynamics underlying plant-microbe interactions. RNA sequencing (RNA-seq) poses technical hurdles in the transcriptional analysis of plant-bacterial interactions, especially in bacterial transcriptomics, owing to the presence of abundant ribosomal RNA (rRNA), which potentially limits the coverage of essential transcripts. Therefore, to achieve cost-effective and comprehensive sequencing of the bacterial transcriptome, it is imperative to devise efficient methods for eliminating rRNA and enhancing the proportion of bacterial mRNA. In this study, we modified a strand-specific dual RNA-seq method with the goal of enriching the proportion of bacterial mRNA in the bacteria-infected plant samples. The enriched method involved the sequential separation of plant mRNA by poly A selection and rRNA removal for bacterial mRNA enrichment followed by strand specific RNA-seq library preparation steps. We assessed the efficiency of the enriched method in comparison to the conventional method by employing various plant-bacterial interactions, including both host and non-host resistance interactions with pathogenic bacteria, as well as an interaction with a beneficial rhizosphere associated bacteria using pepper and tomato plants respectively.ResultsIn all cases of plant-bacterial interactions examined, an increase in mapping efficiency was observed with the enriched method although it produced a lower read count. Especially in the compatible interaction with Xanthmonas campestris pv. Vesicatoria race 3 (Xcv3), the enriched method enhanced the mapping ratio of Xcv3-infected pepper samples to its own genome (15.09%; 1.45-fold increase) and the CDS (8.92%; 1.49-fold increase). The enriched method consistently displayed a greater number of differentially expressed genes (DEGs) than the conventional RNA-seq method at all fold change threshold levels investigated, notably during the early stages of Xcv3 infection in peppers. The Gene Ontology (GO) enrichment analysis revealed that the DEGs were predominantly enriched in proteolysis, kinase, serine type endopeptidase and heme binding activities.ConclusionThe enriched method demonstrated in this study will serve as a suitable alternative to the existing RNA-seq method to enrich bacterial mRNA and provide novel insights into the intricate transcriptomic alterations within the plant-bacterial interplay.

Immunoactive signatures of circulating tRNA- and rRNA-derived RNAs in chronic obstructive pulmonary disease.

Chronic obstructive pulmonary disease (COPD) is the most prevalent lung disease, and macrophages play a central role in the inflammatory response in COPD. We here report a comprehensive characterization of circulating short non-coding RNAs (sncRNAs) in plasma from patients with COPD. While circulating sncRNAs are increasingly recognized for their regulatory roles and biomarker potential in various diseases, the conventional RNA-seq method cannot fully capture these circulating sncRNAs due to their heterogeneous terminal structures. By pre-treating the plasma RNAs with T4 polynucleotide kinase, which converts all RNAs to those with RNA-seq susceptible ends (5'-phosphate and 3'-hydroxyl), we comprehensively sequenced a wide variety of non-microRNA sncRNAs, such as 5'-tRNA halves containing a 2',3'-cyclic phosphate. We discovered a remarkable accumulation of the 5'-half derived from tRNA ValCAC in plasma from COPD patients, whereas the 5'-tRNA GlyGCC half is predominant in healthy donors. Further, the 5'-tRNA ValCAC half activates human macrophages via Toll-like receptor 7 and induces cytokine production. Additionally, we identified circulating rRNA-derived fragments that were upregulated in COPD patients and demonstrated their ability to induce cytokine production in macrophages. Our findings provide evidence of circulating, immune-active sncRNAs in patients with COPD, suggesting that they serve as inflammatory mediators in the pathogenesis of COPD.

Hypermethylation and low expression of FOXM1 predisposes women to unexplained recurrent miscarriage by impairing trophoblast stem cell proliferation

Recurrent miscarriage (RM) is a distressing pregnancy complication with an unknown etiology. Increasing evidence indicates the relevance of dysregulation of human trophoblast stem cells (hTSCs), which may play a role in the development of RM. However, the potential molecular regulatory mechanism underlying the initiation and maintenance of hTSCs is yet to be fully elucidated. In this study, we performed data analysis and identified Forkhead box M1 (FOXM1) as a potential factor associated with RM. FOXM1 is a typical transcription factor known for its involvement in various pathophysiological processes, while the precise function of FOXM1 functions in hTSCs and RM remains incompletely understood. Utilizing RNA-seq, CUT&Tag, ChIP-qPCR, and sodium bisulfite conversion methods for methylation analysis, we elucidate the underlying regulatory mechanisms of FOXM1 in hTSCs and its implications in RM. Our findings demonstrate the relative high expression of FOXM1 in proliferating cytotrophoblasts (CTBs) compared to differentiated extravillous cytotrophoblasts (EVTs) and syncytiotrophoblasts (STBs). Besides, we provide evidence supporting a significant correlation between FOXM1 downregulation and the incidence of RM. Furthermore, we demonstrate the significant role of FOXM1 in regulating hTSCs proliferation and cell cycle through the transcriptional regulation of CDKN3, CCNB2, CCNA2, MAD2L1 and CDC25C. Notably, we observed a correlation between the downregulation of FOXM1 in RM and hypermethylation in its promoter region. Collectively, these results provide insights into the impact of FOXM1 on trophoblast regulation and offer a novel perspective on RM.

Systematic assessment of long-read RNA-seq methods for transcript identification and quantification

The Long-read RNA-Seq Genome Annotation Assessment Project Consortium was formed to evaluate the effectiveness of long-read approaches for transcriptome analysis. Using different protocols and sequencing platforms, the consortium generated over 427 million long-read sequences from complementary DNA and direct RNA datasets, encompassing human, mouse and manatee species. Developers utilized these data to address challenges in transcript isoform detection, quantification and de novo transcript detection. The study revealed that libraries with longer, more accurate sequences produce more accurate transcripts than those with increased read depth, whereas greater read depth improved quantification accuracy. In well-annotated genomes, tools based on reference sequences demonstrated the best performance. Incorporating additional orthogonal data and replicate samples is advised when aiming to detect rare and novel transcripts or using reference-free approaches. This collaborative study offers a benchmark for current practices and provides direction for future method development in transcriptome analysis.

A novel lncRNA associated with the prognosis of patients with colorectal cancer resists apoptosis through the LYN/BCL-2 pathway

PurposeWe found a novel lncRNA named lncAC138150.2 related to the overall survival and staging of patients with colorectal cancer (CRC) by bioinformatic analysis using data from the Cancer Genome Atlas (TCGA), and the study aimed to elucidate the function of lncAC138150.2 and underlying mechanisms. MethodsTarget molecules were knocked down by transfection with antisense oligonucleotides (ASOs), siRNAs, or lentiviruses and overexpressed by transfection with plasmids. The function of lncAC138150.2 was determined using histological, cytological, and molecular biology methods. The underlying mechanism of lncAC138150.2 function was investigated using RNA-seq, bioinformatics analysis, and molecular biology methods. ResultsThe expression of lncAC138150.2 was increased in colorectal tissues compared with paired normal tissues. The lncAC138150.2 knockdown increased apoptosis but did not change the cell proliferation, cell cycle distribution, or cell migration ability of CRC cells, while lncAC138150.2 overexpression decreased CRC apoptosis. lncAC138150.2 was mainly located in the cell nucleus, and each lncAC138150.2 transcript knockdown increased CRC apoptosis. BCL-2 pathway was significantly altered in apoptosis induced by lncAC138150.2 knockdown, which was alleviated by BAX knockdown. The expression of LYN was significantly decreased with lncAC138150.2 knockdown, LYN knockdown increased CRC apoptosis, and its overexpression completely alleviated CRC apoptosis induced by lncAC138150.2 knockdown. ConclusionlncAC138150.2 significantly inhibited CRC apoptosis and affected the prognosis of patients with CRC, through the LYN/BCL-2 pathway.

Integrative analysis of Iso-Seq and RNA-seq data reveals transcriptome complexity and differential isoform in skin tissues of different hair length Yak

BackgroundThe hair follicle development process is regulated by sophisticated genes and signaling networks, and the hair grows from the hair follicle. The Tianzhu white yak population exhibits differences in hair length, especially on the forehead and shoulder region. However, the genetic mechanism is still unclear. Isoform sequencing (Iso-seq) technology with advantages in long reads sequencing. Hence, we combined the Iso-seq and RNA-seq methods to investigate the transcript complexity and difference between long-haired yak (LHY) and normal-haired yak (NHY).ResultsThe hair length measurement result showed a significant difference between LHY and NHY on the forehead and the shoulder (P-value < 0.001). The skin samples from the forehead and the shoulder of LHY and NHY were pooled for isoform sequencing (Iso-seq). We obtained numerous long transcripts, including novel isoforms, long non-coding RNA, alternative splicing events, and alternative polyadenylation events. Combined with RNA-seq data, we performed differential isoforms (DEIs) analysis between LHY and NHY. We found that some hair follicle and skin development-related DEIs, like BMP4, KRT2, IGF2R, and COL1A2 in the forehead skin; BMP1, KRT1, FGF5, COL2A1, and IGFBP5 in the shoulder skin. Enrichment analysis revealed that DEIs in both two comparable groups significantly participated in skin and hair follicle development-related pathways, like ECM-receptor interaction, focal adhesion, and PI3K-Akt signaling pathways. The results indicated that the hair follicle development of Tianzhu white yak may influence the hair length difference. Besides, the protein-protein interaction (PPI) network of DEIs showed COL2A1 and COL3A1 exhibited a high degree of centrality, and these two genes were suggested as potential candidates for the hair length growth of Tianzhu white yak.ConclusionsThe results provided a comprehensive analysis of the transcriptome complexity and identified differential transcripts that enhance our understanding of the molecular mechanisms underlying the variation in hair length growth in Tianzhu white yak.

Identification of key genes affecting ventilator-induced diaphragmatic dysfunction in diabetic mice.

Mechanical ventilation (MV) is often required in critically ill patients. However, prolonged mechanical ventilation can lead to Ventilator-induced diaphragmatic dysfunction (VIDD), resulting in difficulty in extubation after tracheal intubation, prolonged ICU stay, and increased mortality. At present, the incidence of diabetes is high in the world, and the prognosis of diabetic patients with mechanical ventilation is generally poor. Therefore, the role of diabetes in the development of VIDD needs to be discovered. MV modeling was performed on C57 mice and DB mice, and the control group was set up in each group. After 12h of mechanical ventilation, the muscle strength of the diaphragm was measured, and the muscle fiber immunofluorescence staining was used to verify the successful establishment of the MV model. RNA sequencing (RNA-seq) method was used to detect mRNA expression levels of the diaphragms of each group, and then differential expressed gene analysis, Heatmap analysis, WGCNA analysis, Venn analysis, GO and KEGG enrichment analysis were performed. qRT-PCR was used to verify the expression of the selected mRNAs. Our results showed that, compared with C57 control mice, the muscle strength and muscle fiber cross-sectional area of mice after mechanical ventilation decreased, and DB mice showed more obvious in this respect. RNA-seq showed that these differential expressed (DE) mRNAs were mainly related to genes such as extracellular matrix, collagen, elastic fiber and Fbxo32. GO and KEGG enrichment analysis showed that the signaling pathways associated with diabetes were mainly as follows: extracellular matrix (ECM), protein digestion and absorption, PI3K-Akt signaling pathway, calcium signaling pathway, MAPK signaling pathway and AGE-RAGE signaling pathway in diabetic complications, etc. ECM has the closest relationship with VIDD in diabetic mice. The key genes determined by WGCNA and Venn analysis were validated by quantitative real-time polymerase chain reaction (qRT-PCR), which exhibited trends similar to those observed by RNA-seq. VIDD can be aggravated in diabetic environment. This study provides new evidence for mRNA changes after mechanical ventilation in diabetic mice, suggesting that ECM and collagen may play an important role in the pathophysiological mechanism and progression of VIDD in diabetic mice, and provides some clues for the research, diagnosis, and treatment of VIDD in diabetic context.

Transcriptomics coupled with proteomics reveals osimertinib-induced myocardial mitochondrial dysfunction

Osimertinib, an irreversible epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI) used for cancer treatment, can cause significant cardiac toxicity. However, the specific mechanism of osimertinib-induced cardiotoxicity is not fully understood. In this study, we administered osimertinib to mice and neonatal rat ventricular myocytes (NRVMs). We observed significant structural and functional damage to the hearts of these mice, along with a marked increase in cardiac injury biomarkers and accompanying ultrastructural damage to mitochondria. We integrated 4D label-free protein quantification and RNA-Seq methods to analyze the sequencing data of NRVMs under osimertinib treatment (0 and 2.5 μM). Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis evidenced that differentially expressed genes (DEGs)and differentially expressed proteins (DEPs) were distinctly enriched for oxidative phosphorylation (OXPHOs). Simultaneously, osimertinib primarily affected the contents of adenosine triphosphate (ATP). Further investigations revealed that osimertinib disrupts the functions of the ATP synthase (complex V), leading to a reduction in ATP production. Taken together, our data demonstrated that osimertinib causes mitochondrial dysfunction, which in turn leads to the onset of cardiac toxicity.

Transcriptomic and metabolomic dissection of skeletal muscle of crossbred Chongming white goats with different meat production performance

BackgroundThe transcriptome and metabolome dissection of the skeletal muscle of high- and low- growing individuals from a crossbred population of the indigenous Chongming white goat and the Boer goat were performed to discover the potential functional differentially expressed genes (DEGs) and differential expression metabolites (DEMs).ResultsA total of 2812 DEGs were detected in 6 groups at three time stages (3,6,12 Month) in skeletal muscle using the RNA-seq method. A DEGs set containing seven muscle function related genes (TNNT1, TNNC1, TNNI1, MYBPC2, MYL2, MHY7, and CSRP3) was discovered, and their expression tended to increase as goat muscle development progressed. Seven DEGs (TNNT1, FABP3, TPM3, DES, PPP1R27, RCAN1, LMOD2) in the skeletal muscle of goats in the fast-growing and slow-growing groups was verified their expression difference by reverse transcription-quantitative polymerase chain reaction. Further, through the Liquid chromatography-mass spectrometry (LC-MS) approach, a total of 183 DEMs in various groups of the muscle samples and these DEMs such as Queuine and Keto-PGF1α, which demonstrated different abundance between the goat fast-growing group and slow-growing group. Through weighted correlation network analysis (WGCNA), the study correlated the DEGs with the DEMs and identified 4 DEGs modules associated with 18 metabolites.ConclusionThis study benefits to dissection candidate genes and regulatory networks related to goat meat production performance, and the joint analysis of transcriptomic and metabolomic data provided insights into the study of goat muscle development.

Comparative transcriptomic profiling of the two-stage response of rice to Xanthomonas oryzae pv. oryzicola interaction with two different pathogenic strains.

Two-tiered plant immune responses involve cross-talk among defense-responsive (DR) genes involved in pathogen-associated molecular pattern (PAMP)-triggered immunity (PTI), effector-triggered immunity (ETI) and effector-triggered susceptibility (ETS). Bacterial leaf streak (BLS), caused by Xanthomonas oryzae pv. oryzicola (Xoc) is an important bacterial disease that causes serious threats to rice yield and quality. Transcriptomic profiling provides an effective approach for the comprehensive and large-scale detection of DR genes that participate in the interactions between rice and Xoc. In this study, we used RNA-seq to analyze the differentially expressed genes (DEGs) in susceptible rice after inoculation with two naturally pathogenic Xoc strains, a hypervirulent strain, HGA4, and a relatively hypovirulent strain, RS105. First, bacterial growth curve and biomass quantification revealed that differential growth occurred beginning at 1day post inoculation (dpi) and became more significant at 3 dpi. Additionally, we analyzed the DEGs at 12h and 3 days post inoculation with two strains, representing the DR genes involved in the PTI and ETI/ETS responses, respectively. Gene Ontology (GO) functional and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed on the common DEGs, which included 4380 upregulated and 4019 downregulated genes and 930 upregulated and 1383 downregulated genes identified for the two strains at 12h post inoculation (hpi) and 3 dpi, respectively. Compared to those at 12 hpi, at 3 dpi the number of common DEGs decreased, while the degree of differential expression was intensified. In addition, more disease-related GO pathways were enriched, and more transcription activator-like effector (TALE) putative target genes were upregulated in plants inoculated with HGA4 than in those inoculated with RS105 at 3 dpi. Then, four DRs were randomly selected for the BLS resistance assay. We found that CDP3.10, LOC_Os11g03820, and OsDSR2 positively regulated rice resistance to Xoc, while OsSPX3 negatively regulated rice resistance. By using an enrichment method for RNA-seq, we identified a group of DEGs related to the two stages of response to the Xoc strain, which included four functionally identified DR genes.

CASCC: a co-expression-assisted single-cell RNA-seq data clustering method.

Existing clustering methods for characterizing cell populations from single-cell RNA sequencing are constrained by several limitations stemming from the fact that clusters often cannot be homogeneous, particularly for transitioning populations. On the other hand, dominant cell populations within samples can be identified independently by their strong gene co-expression signatures using methods unrelated to partitioning. Here, we introduce a clustering method, CASCC (co-expression-assisted single-cell clustering), designed to improve biological accuracy using gene co-expression features identified using an unsupervised adaptive attractor algorithm. CASCC outperformed other methods as evidenced by multiple evaluation metrics, and our results suggest that CASCC can improve the analysis of single-cell transcriptomics, enabling potential new discoveries related to underlying biological mechanisms. The CASCC R package is publicly available at https://github.com/LingyiC/CASCC and https://zenodo.org/doi/10.5281/zenodo.10648327.