Dynamic repertoire of a eukaryotic transcriptome surveyed at single-nucleotide resolution

Decoding the molecular concerto: Toxicotranscriptomic evaluation of microplastic and nanoplastic impacts on aquatic organisms

The pervasive and steadily increasing presence of microplastics/nanoplastics (MPs/NPs) in aquatic environments has raised significant concerns regarding their potential adverse effects on aquatic organisms and their integration into trophic dynamics. This emerging issue has garnered the attention of (eco)toxicologists, promoting the utilization of toxicotranscriptomics to unravel the responses of aquatic organisms not only to MPs/NPs but also to a wide spectrum of environmental pollutants. This review aims to systematically explore the broad repertoire of predicted molecular responses by aquatic organisms, providing valuable intuitions into complex interactions between plastic pollutants and aquatic biota. By synthesizing the latest literature, present analysis sheds light on transcriptomic signatures like gene expression, interconnected pathways and overall molecular mechanisms influenced by various plasticizers. Harmful effects of these contaminants on key genes/protein transcripts associated with crucial pathways lead to abnormal immune response, metabolic response, neural response, apoptosis and DNA damage, growth, development, reproductive abnormalities, detoxification, and oxidative stress in aquatic organisms. However, unique challenge lies in enhancing the fingerprint of MPs/NPs, presenting complicated enigma that requires decoding their specific impact at molecular levels. The exploration endeavors, not only to consolidate existing knowledge, but also to identify critical gaps in understanding, push forward the frontiers of knowledge about transcriptomic signatures of plastic contaminants. Moreover, this appraisal emphasizes the imperative to monitor and mitigate the contamination of commercially important aquatic species by MPs/NPs, highlighting the pivotal role that regulatory frameworks must play in protecting all aquatic ecosystems. This commitment aligns with the broader goal of ensuring the sustainability of aquatic resources and the resilience of ecosystems facing the growing threat of plastic pollutants.

Short-Read RNA-Seq

RNA sequencing (RNA-Seq) has emerged as a powerful and versatile tool for the comprehensive analysis of transcriptomes and has been widely used to investigate gene expression, copy number variation, alternative splicing, and novel transcript discovery. This chapter outlines the methodology for conducting short-read RNA-Seq, starting from RNA enrichment to library preparation and sequencing. Throughout the chapter, practical tips and best practices are provided to guide researchers in order to optimize each step of the RNA-Seq workflow. Multiple quality control steps throughout the workflow that are critical to obtain high-quality RNA-Seq data are also discussed.

A role for the carbon source of the cell and protein kinase A in regulating the S. pombe septation initiation network

The septation initiation network (SIN) is a conserved signal transduction network, which is important for cytokinesis in Schizosaccharomyces pombe. The SIN component Etd1p is required for association of some SIN proteins with the spindle pole body (SPB) during anaphase and for contractile ring formation. We show that tethering of Cdc7p or Sid1p to the SIN scaffold Cdc11p at the SPB, rescues etd1-Δ. Analysis of a suppressor of the mutant etd1-M9 revealed that SIN signalling is influenced by the carbon source of the cell. Growth on a non-fermentable carbon source glycerol reduces the requirement for SIN signalling but does not bypass it. The decreased need for SIN signalling is mediated largely by reduction of protein kinase A activity, and it is phenocopied by deletion of pka1 on glucose medium. We conclude that protein kinase A is an important regulator of the SIN, and that SIN signalling is regulated by the carbon source of the cell.

Approaches and challenges in genome-wide circular RNA identification and quantification

Numerous circular RNAs (circRNAs) produced from back-splicing of exon(s) have been recently revealed on a genome-wide scale across species. Although generally expressed at a low level, some relatively abundant circRNAs can play regulatory roles in various biological processes, prompting continuous profiling of circRNA in broader conditions. Over the past decade, distinct strategies have been applied in both transcriptome enrichment and bioinformatic tools for detecting and quantifying circRNAs. Understanding the scope and limitations of these strategies is crucial for the subsequent annotation and characterization of circRNAs, especially those with functional potential. Here, we provide an overview of different transcriptome enrichment, deep sequencing and computational approaches for genome-wide circRNA identification, and discuss strategies for accurate quantification and characterization of circRNA.

Diagnosis in Scrapie: Conventional Methods and New Biomarkers

Scrapie, a naturally occurring prion disease affecting goats and sheep, comprises classical and atypical forms, with classical scrapie being the archetype of transmissible spongiform encephalopathies. This review explores the challenges of scrapie diagnosis and the utility of various biomarkers and their potential implications for human prion diseases. Understanding these biomarkers in the context of scrapie may enable earlier prion disease diagnosis in humans, which is crucial for effective intervention. Research on scrapie biomarkers bridges the gap between veterinary and human medicine, offering hope for the early detection and improved management of prion diseases.

Lower Airway Dysbiosis Augments Lung Inflammatory Injury in Mild-to-Moderate Chronic Obstructive Pulmonary Disease

Rationale: Chronic obstructive pulmonary disease (COPD) is associated with high morbidity, mortality, and healthcare costs. Cigarette smoke is a causative factor; however, not all heavy smokers develop COPD. Microbial colonization and infections are contributing factors to disease progression in advanced stages. Objectives: We investigated whether lower airway dysbiosis occurs in mild-to-moderate COPD and analyzed possible mechanistic contributions to COPD pathogenesis. Methods: We recruited 57 patients with a >10 pack-year smoking history: 26 had physiological evidence of COPD, and 31 had normal lung function (smoker control subjects). Bronchoscopy sampled the upper airways, lower airways, and environmental background. Samples were analyzed by 16S rRNA gene sequencing, whole genome, RNA metatranscriptome, and host RNA transcriptome. A preclinical mouse model was used to evaluate the contributions of cigarette smoke and dysbiosis on lower airway inflammatory injury. Measurements and Main Results: Compared with smoker control subjects, microbiome analyses showed that the lower airways of subjects with COPD were enriched with common oral commensals. The lower airway host transcriptomics demonstrated differences in markers of inflammation and tumorigenesis, such as upregulation of IL-17, IL-6, ERK/MAPK, PI3K, MUC1, and MUC4 in mild-to-moderate COPD. Finally, in a preclinical murine model exposed to cigarette smoke, lower airway dysbiosis with common oral commensals augments the inflammatory injury, revealing transcriptomic signatures similar to those observed in human subjects with COPD. Conclusions: Lower airway dysbiosis in the setting of smoke exposure contributes to inflammatory injury early in COPD. Targeting the lower airway microbiome in combination with smoking cessation may be of potential therapeutic relevance.

Unveiling the novel immune and molecular signatures of ovarian cancer: insights and innovations from single-cell sequencing

Ovarian cancer is a highly heterogeneous and lethal malignancy with limited treatment options. Over the past decade, single-cell sequencing has emerged as an advanced biological technology capable of decoding the landscape of ovarian cancer at the single-cell resolution. It operates at the level of genes, transcriptomes, proteins, epigenomes, and metabolisms, providing detailed information that is distinct from bulk sequencing methods, which only offer average data for specific lesions. Single-cell sequencing technology provides detailed insights into the immune and molecular mechanisms underlying tumor occurrence, development, drug resistance, and immune escape. These insights can guide the development of innovative diagnostic markers, therapeutic strategies, and prognostic indicators. Overall, this review provides a comprehensive summary of the diverse applications of single-cell sequencing in ovarian cancer. It encompasses the identification and characterization of novel cell subpopulations, the elucidation of tumor heterogeneity, the investigation of the tumor microenvironment, the analysis of mechanisms underlying metastasis, and the integration of innovative approaches such as organoid models and multi-omics analysis.

Transcriptomic and Physiological Analysis Reveals Genes Associated with Drought Stress Responses in Populus alba × Populus glandulosa

Drought stress affects plant productivity by altering plant responses at the morphological, physiological, and molecular levels. In this study, we identified physiological and genetic responses in Populus alba × Populus glandulosa hybrid clones 72-30 and 72-31 after 12 days of exposure to drought treatment. After 12 days of drought treatment, glucose, fructose, and sucrose levels were significantly increased in clone 72-30 under drought stress. The Fv/Fo and Fv/Fm values in both clones also decreased under drought stress. The changes in proline, malondialdehyde, and H2O2 levels were significant and more pronounced in clone 72-30 than in clone 72-31. The activities of antioxidant-related enzymes, such as catalase and ascorbate peroxidase, were significantly higher in the 72-31 clone. To identify drought-related genes, we conducted a transcriptomic analysis in P. alba × P. glandulosa leaves exposed to drought stress. We found 883 up-regulated and 305 down-regulated genes in the 72-30 clone and 279 and 303 in the 72-31 clone, respectively. These differentially expressed genes were mainly in synthetic pathways related to proline, abscisic acid, and antioxidants. Overall, clone 72-31 showed better drought tolerance than clone 72-30 under drought stress, and genetic changes also showed different patterns.

Multi-Omics Profiling for Health

The world has witnessed a steady rise in both non-infectious and infectious chronic diseases, prompting a cross-disciplinary approach to understand and treating disease. Current medical care focuses on treating people after they become patients rather than preventing illness, leading to high costs in treating chronic and late-stage diseases. Additionally, a "one-size-fits all" approach to health care does not take into account individual differences in genetics, environment, or lifestyle factors, decreasing the number of people benefiting from interventions. Rapid advances in omics technologies and progress in computational capabilities have led to the development of multi-omics deep phenotyping, which profiles the interaction of multiple levels of biology over time and empowers precision health approaches. This review highlights current and emerging multi-omics modalities for precision health and discusses applications in the following areas: genetic variation, cardio-metabolic diseases, cancer, infectious diseases, organ transplantation, pregnancy, and longevity/aging. We will briefly discuss the potential of multi-omics approaches in disentangling host-microbe and host-environmental interactions. We will touch on emerging areas of electronic health record and clinical imaging integration with muti-omics for precision health. Finally, we will briefly discuss the challenges in the clinical implementation of multi-omics and its future prospects.

Somatosensory neuron types and their neural networks as revealed via single-cell transcriptomics

Single-cell RNA sequencing (scRNA-seq) has allowed profiling cell types of the dorsal root ganglia (DRG) and their transcriptional states in physiology and chronic pain. However, the evaluation criteria used in previous studies to classify DRG neurons varied, which presents difficulties in determining the various types of DRG neurons. In this review, we aim to integrate findings from previous transcriptomic studies of the DRG. We first briefly introduce the history of DRG-neuron cell-type profiling, and discuss the advantages and disadvantages of different scRNA-seq methods. We then examine the classification of DRG neurons based on single-cell profiling under physiological and pathological conditions. Finally, we propose further studies on the somatosensory system at the molecular, cellular, and neural network levels.

The Effect of the Feeding System on Fat Deposition in Yak Subcutaneous Fat

Fat deposition is very important to the growth and reproduction of yaks. In this study, the effect of the feeding system on fat deposition in yaks was explored by transcriptomics and lipidomics. The thickness of the subcutaneous fat in yaks under stall (SF) and graze feeding (GF) was evaluated. The transcriptomes and lipidomes of the subcutaneous fat in yaks under different feeding systems were detected by RNA-sequencing (RNA-Seq) and non-targeted lipidomics based on ultrahigh-phase liquid chromatography tandem mass spectrometry (UHPLC-MS), respectively. The differences in lipid metabolism were explored, and the function of differentially expressed genes (DEGs) was evaluated by gene ontology (GO) and Kyoto encyclopedia of genes and genome (KEGG) analysis. Compared with GF yaks, SF yaks possessed stronger fat deposition capacity. The abundance of 12 triglycerides (TGs), 3 phosphatidylethanolamines (PEs), 3 diglycerides (DGs), 2 sphingomyelins (SMs) and 1 phosphatidylcholine (PC) in the subcutaneous fat of SF and GF yaks was significantly different. Under the mediation of the cGMP-PKG signaling pathway, the blood volume of SF and GF yaks may be different, which resulted in the different concentrations of precursors for fat deposition, including non-esterified fatty acid (NEFA), glucose (GLU), TG and cholesterol (CH). The metabolism of C16:0, C16:1, C17:0, C18:0, C18:1, C18:2 and C18:3 in yak subcutaneous fat was mainly realized under the regulation of the INSIG1, ACACA, FASN, ELOVL6 and SCD genes, and TG synthesis was regulated by the AGPAT2 and DGAT2 genes. This study will provide a theoretical basis for yak genetic breeding and healthy feeding.

Transcriptome Sequencing Reveals Salmonella Flagellin Activation of Interferon-β-Related Immune Responses in Macrophages

The flagellin (FliC) of Salmonella typhimurium is a potential vaccine adjuvant as it can activate innate immunity and promote acquired immune responses. Macrophages are an important component of the innate immune system. The mechanism of flagellin’s adjuvant activity has been shown to be related to its ability to activate macrophages. However, few studies have comprehensively investigated the effects of Salmonella flagellin in macrophages using transcriptome sequencing. In this study, RNA-Seq was used to analyze the expression patterns of RAW264.7 macrophages induced by FliC to identify novel transcriptomic signatures in macrophages. A total of 2204 differentially expressed genes were found in the FliC-treated group compared with the control. Gene ontology and KEGG pathway analyses identified the top significantly regulated functional classification and canonical pathways, which were mainly related to immune responses and regulation. Inflammatory cytokines (IL-6, IL-1β, TNF-α, etc.) and chemokines (CXCL2, CXCL10, CCL2, etc.) were highly expressed in RAW264.7 cells following stimulation. Notably, flagellin significantly increased the expression of interferon (IFN)-β. In addition, previously unidentified IFN regulatory factors (IRFs) and IFN-stimulated genes (ISGs) were also significantly upregulated. The results of RNA-Seq were verified, and furthermore, we demonstrated that flagellin increased the expression of IFN-β and IFN-related genes (IRFs and ISGs) in bone marrow-derived dendritic cells and macrophages. These results suggested that Salmonella flagellin can activate IFN-β-related immune responses in macrophages, which provides new insight into the immune mechanisms of flagellin adjuvant.

Simultaneous Single-Cell Profiling of the Transcriptome and Accessible Chromatin Using SHARE-seq

The ability to analyze the transcriptomic and epigenomic states of individual single cells has in recent years transformed our ability to measure and understand biological processes. Recent advancements have focused on increasing sensitivity and throughput to provide richer and deeper biological insights at the cellular level. The next frontier is the development of multiomic methods capable of analyzing multiple features from the same cell, such as the simultaneous measurement of the transcriptome and the chromatin accessibility of candidate regulatory elements. In this chapter, we discuss and describe SHARE-seq (Simultaneous high-throughput ATAC, and RNA expression with sequencing) for carrying out simultaneous chromatin accessibility and transcriptome measurements in single cells, together with the experimental and analytical considerations for achieving optimal results.

Single-cell RNA sequencing in orthopedic research

Although previous RNA sequencing methods have been widely used in orthopedic research and have provided ideas for therapeutic strategies, the specific mechanisms of some orthopedic disorders, including osteoarthritis, lumbar disc herniation, rheumatoid arthritis, fractures, tendon injuries, spinal cord injury, heterotopic ossification, and osteosarcoma, require further elucidation. The emergence of the single-cell RNA sequencing (scRNA-seq) technique has introduced a new era of research on these topics, as this method provides information regarding cellular heterogeneity, new cell subtypes, functions of novel subclusters, potential molecular mechanisms, cell-fate transitions, and cell‒cell interactions that are involved in the development of orthopedic diseases. Here, we summarize the cell subpopulations, genes, and underlying mechanisms involved in the development of orthopedic diseases identified by scRNA-seq, improving our understanding of the pathology of these diseases and providing new insights into therapeutic approaches.

Gene expression prediction based on neighbour connection neural network utilizing gene interaction graphs

Having observed that gene expressions have a correlation, the Library of Integrated Network-based Cell-Signature program selects 1000 landmark genes to predict the remaining gene expression value. Further works have improved the prediction result by using deep learning models. However, these models ignore the latent structure of genes, limiting the accuracy of the experimental results. We therefore propose a novel neural network named Neighbour Connection Neural Network(NCNN) to utilize the gene interaction graph information. Comparing to the popular GCN model, our model incorperates the graph information in a better manner. We validate our model under two different settings and show that our model promotes prediction accuracy comparing to the other models.

Attempts for deriving extended pluripotent stem cells from common marmoset embryonic stem cells

Extended pluripotent stem cells (EPSCs) derived from mice and humans showed an enhanced potential for chimeric formation. By exploiting transcriptomic approaches, we assessed the differences in gene expression profile between extended EPSCs derived from mice and humans, and those newly derived from the common marmoset (marmoset; Callithrix jacchus). Although the marmoset EPSC-like cells displayed a unique colony morphology distinct from murine and human EPSCs, they displayed a pluripotent state akin to embryonic stem cells (ESCs), as confirmed by gene expression and immunocytochemical analyses of pluripotency markers and three-germ-layer differentiation assay. Importantly, the marmoset EPSC-like cells showed interspecies chimeric contribution to mouse embryos, such as E6.5 blastocysts in vitro and E6.5 epiblasts in vivo in mouse development. Also, we discovered that the perturbation of gene expression of the marmoset EPSC-like cells from the original ESCs resembled that of human EPSCs. Taken together, our multiple analyses evaluated the efficacy of the method for the derivation of marmoset EPSCs.

Monitoring Mechano-Regulation of Gene Expression by RNA Sequencing

The advent of high-throughput sequencing techniques has revolutionized biological research. One such method is RNA sequencing, which has become a relatively affordable and routine method for quantifying and comparing gene expression changes over desired experimental conditions. Along with the popularity of the method, a myriad of user-friendly, open-source computational tools have also emerged for differential gene expression analyses. Correspondingly, decades of mechanobiology research have established that mechanical cues, both alone and/or in combination with biochemical signals, can be powerful regulators of transcriptional programs and consequently cell state/fate transitions. Thus, it has become possible to investigate both universal and specific temporally resolved transcriptional responses upon mechanical stimulation genome-wide. This chapter will describe methods to analyze transcriptional changes in response to extrinsic mechanical stretch.

RNA Preparation and RNA-Seq Bioinformatics for Comparative Transcriptomics

The principal transcriptome analysis is the determination of differentially expressed genes across experimental conditions. For this, the next-generation sequencing of RNA (RNA-seq) has several advantages over other techniques, such as the capability of detecting all the transcripts in one assay over RT-qPCR, such as its higher accuracy and broader dynamic range over microarrays or the ability to detect novel transcripts, including non-coding RNA molecules, at nucleotide-level resolution over both techniques. Despite these advantages, many microbiology laboratories have not yet applied RNA-seq analyses to their investigations. The high cost of the equipment for next-generation sequencing is no longer an issue since this intermediate part of the analysis can be provided by commercial or central services. Here, we detail a protocol for the first part of the analysis, the RNA extraction and an introductory protocol to the bioinformatics analysis of the sequencing data to generate the differential expression results.

Temporal progress of gene expression analysis with RNA-Seq data: A review on the relationship between computational methods

Analysis of differential gene expression from RNA-seq data has become a standard for several research areas. The steps for the computational analysis include many data types and file formats, and a wide variety of computational tools that can be applied alone or together as pipelines. This paper presents a review of the differential expression analysis pipeline, addressing its steps and the respective objectives, the principal methods available in each step, and their properties, therefore introducing an organized overview to this context. This review aims to address mainly the aspects involved in the differentially expressed gene (DEG) analysis from RNA sequencing data (RNA-seq), considering the computational methods. In addition, a timeline of the computational methods for DEG is shown and discussed, and the relationships existing between the most important computational tools are presented by an interaction network. A discussion on the challenges and gaps in DEG analysis is also highlighted in this review. This paper will serve as a tutorial for new entrants into the field and help established users update their analysis pipelines.

Non-coding antisense transcripts: fine regulation of gene expression in cancer

Natural antisense transcripts (NATs) are coding or non-coding RNA sequences transcribed on the opposite direction from the same genomic locus. NATs are widely distributed throughout the human genome and seem to play crucial roles in physiological and pathological processes, through newly described and targeted mechanisms. NATs represent the intricate complexity of the genome organization and constitute another layer of potential targets in disease. Here, we focus on the interesting and unique role of non-coding NATs in cancer, paying particular attention to those acting as miRNA sponges.

Severe, but not moderate asthmatics share blood transcriptomic changes with post-traumatic stress disorder and depression

Asthma, an inflammatory disorder of the airways, is one of the most common chronic illnesses worldwide and is associated with significant morbidity. There is growing recognition of an association between asthma and mood disorders including post-traumatic stress disorder (PTSD) and major depressive disorder (MDD). Although there are several hypotheses regarding the relationship between asthma and mental health, there is little understanding of underlying mechanisms and causality. In the current study we utilized publicly available datasets of human blood mRNA collected from patients with severe and moderate asthma, MDD, and PTSD. We performed differential expression (DE) analysis and Gene Set Enrichment Analysis (GSEA) on diseased subjects against the healthy subjects from their respective datasets, compared the results between diseases, and validated DE genes and gene sets with 4 more independent datasets. Our analysis revealed that commonalities in blood transcriptomic changes were only found between the severe form of asthma and mood disorders. Gene expression commonly regulated in PTSD and severe asthma, included ORMDL3 a gene known to be associated with asthma risk and STX8, which is involved in TrkA signaling. We also identified several pathways commonly regulated to both MDD and severe asthma. This study reveals gene and pathway regulation that potentially drives the comorbidity between severe asthma, PTSD, and MDD and may serve as foci for future research aimed at gaining a better understanding of both the relationship between asthma and PTSD, and the pathophysiology of the individual disorders.

Biogenesis and Regulatory Roles of Circular RNAs

Covalently closed, single-stranded circular RNAs can be produced from viral RNA genomes as well as from the processing of cellular housekeeping noncoding RNAs and precursor messenger RNAs. Recent transcriptomic studies have surprisingly uncovered that many protein-coding genes can be subjected to backsplicing, leading to widespread expression of a specific type of circular RNAs (circRNAs) in eukaryotic cells. Here, we discuss experimental strategies used to discover and characterize diverse circRNAs at both the genome and individual gene scales. We further highlight the current understanding of how circRNAs are generated and how the mature transcripts function. Some circRNAs act as noncoding RNAs to impact gene regulation by serving as decoys or competitors for microRNAs and proteins. Others form extensive networks of ribonucleoprotein complexes or encode functional peptides that are translated in response to certain cellular stresses. Overall, circRNAs have emerged as an important class of RNAmolecules in gene expression regulation that impact many physiological processes, including early development, immune responses, neurogenesis, and tumorigenesis.

Identification of long non-coding RNAs involved in floral scent of Rosa hybrida

Long non-coding RNAs (lncRNAs) were found to play important roles in transcriptional, post-transcriptional, and epigenetic gene regulation in various biological processes. However, lncRNAs and their regulatory roles remain poorly studied in horticultural plants. Rose is economically important not only for their wide use as garden and cut flowers but also as important sources of natural fragrance for perfume and cosmetics industry, but presently little was known about the regulatory mechanism of the floral scent production. In this paper, a RNA-Seq analysis with strand-specific libraries, was performed to rose flowers in different flowering stages. The scented variety 'Tianmidemeng' (Rosa hybrida) was used as plant material. A total of 13,957 lncRNAs were identified by mining the RNA-Seq data, including 10,887 annotated lncRNAs and 3070 novel lncRNAs. Among them, 10,075 lncRNAs were predicted to possess a total of 29,622 target genes, including 54 synthase genes and 24 transcription factors related to floral scent synthesis. 425 lncRNAs were differentially expressed during the flowering process, among which 19 were differentially expressed among all the three flowering stages. Using weighted correlation network analysis (WGCNA), we correlate the differentially-expressed lncRNAs to synthesis of individual floral scent compounds. Furthermore, regulatory function of one of candidate lncRNAs for floral scent synthesis was verified using VIGS method in the rose. In this study, we were able to show that lncRNAs may play important roles in floral scent production in the rose. This study also improves our understanding of how plants regulate their secondary metabolism by lncRNAs.

An intersectional analysis of LncRNAs and mRNAs reveals the potential therapeutic targets of Bi Zhong Xiao Decoction in collagen-induced arthritis rats

Background

Bi Zhong Xiao decoction (BZXD), a traditional Chinese herbal formula, has been used clinically for many years to treat rheumatoid arthritis (RA). Both clinical and experimental studies have revealed that BZXD is effective in treating RA, but the mechanism remains unclear. In this study, we aimed to explore the mechanism of efficacy of BZXD through transcriptomic analysis of lncRNA and mRNA.

Methods

The combination method of ultra-high performance liquid chromatography-mass spectrometry/mass spectrometry was used to assess the quality of BZXD. The efficacy of BZXD in treating collagen-induced arthritis (CIA) was evaluated by clinical assessment, weight changes, hematoxylin–eosin and safranin o-fast green staining, and Micro-CT. Arraystar rat lncRNA-mRNA chip technology was used to determine the lncRNA and mRNA expression profiles of the Control, CIA and BZXD groups, and to screen gene expression profiles related to the curative effect of BZXD. A lncRNA-mRNA co-expression network was constructed for the therapeutic efficacy genes. Through GO function and KEGG pathway enrichment analysis, the biological functions and signaling pathways of therapeutic efficacy genes were determined. Based on fold change and functional annotation, key differentially expressed lncRNAs and mRNAs were selected for reverse transcription-quantitative polymerase chain reaction (RT-qPCR) validation. The functions of lncRNAs targeting mRNAs were verified in vitro.

Results

We demonstrated that BZXD could effectively reverse bone erosion. After BZXD treatment, up to 33 lncRNAs and 107 mRNAs differentially expressed genes were reversely regulated by BZXD. These differentially expressed lncRNAs are mainly involved in the biological process of the immune response and are closely related to the ECM-receptor interaction, MAPK signaling pathway, Focal adhesion, Ras signaling pathway, Antigen processing and presentation, and Chemokine signaling pathway. We identified four lncRNAs (uc.361−, ENSRNOT00000092834, ENSRNOT00000089244, ENSRNOT00000084631) and three mRNAs (Acvr2a, Cbx2, Morc4) as potential therapeutic targets for BZXD and their microarray data consistent with the RT-qPCR. In vitro experiments confirmed that silencing the lncRNAs ENSRNOT00000092834 and ENSRNOT00000084631 reversed the expression of target mRNAs.

Conclusions

This study elucidates the possible mechanism of BZXD reversing bone erosion in CIA rats from the perspective of lncRNA and mRNA. To provide a basis and direction for further exploration of the mechanism of BZXD in treating RA.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13020-022-00670-z.

Bioinformatics analysis reveals potential biomarkers associated with the occurrence of intracranial aneurysms

To better understand the molecular mechanisms of intracranial aneurysm (IA) pathogenesis, we used gene coexpression networks to identify hub genes and functional pathways associated with IA onset. Two Gene Expression Omnibus (GEO) datasets encompassing intracranial aneurysm tissue samples and cerebral artery control samples were included. To discover functional pathways and potential biomarkers, weighted gene coexpression network analysis was employed. Next, single-gene gene set enrichment analysis was employed to investigate the putative biological roles of the chosen genes. We also used receiver operating characteristic analysis to confirm the diagnostic results. Finally, we used a rat model to confirm the hub genes in the module of interest. The module of interest, which was designated the green module and included 115 hub genes, was the key module that was most strongly and negatively associated with IA formation. According to gene set variation analysis results, 15 immune-related pathways were significantly activated in the IA group, whereas 7 metabolic pathways were suppressed. In two GEO datasets, SLC2A12 could distinguish IAs from control samples. Twenty-nine hub genes in the green module might be biomarkers for the occurrence of cerebral aneurysms. SLC2A12 expression was significantly downregulated in both human and rat IA tissue. In the present study, we identified 115 hub genes related to the pathogenesis of IA onset and deduced their potential roles in various molecular pathways; this new information may contribute to the diagnosis and treatment of IAs. By external validation, the SLC2A12 gene may play an important role. The molecular function of SLC2A12 in the process of IA occurrence can be further studied in a rat model.

Transcriptome Analysis of Tryptophan-Induced Resistance against Potato Common Scab

Potato common scab (CS) is a worldwide soil-borne disease that severely reduces tuber quality and market value. We observed that foliar application of tryptophan (Trp) could induce resistance against CS. However, the mechanism of Trp as an inducer to trigger host immune responses is still unclear. To facilitate dissecting the molecular mechanisms, the transcriptome of foliar application of Trp and water (control, C) was compared under Streptomyces scabies (S) inoculation and uninoculation. Results showed that 4867 differentially expressed genes (DEGs) were identified under S. scabies uninoculation (C-vs-Trp) and 2069 DEGs were identified under S. scabies inoculation (S-vs-S+Trp). Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses indicated that Trp induced resistance related to the metabolic process, response to stimulus, and biological regulation. As phytohormone metabolic pathways related to inducing resistance, the expression patterns of candidate genes involved in salicylic acid (SA) and jasmonic acid/ethylene (JA/ET) pathways were analyzed using qRT-PCR. Their expression patterns showed that the systemic acquired resistance (SAR) and induced systemic resistance (ISR) pathways could be co-induced by Trp under S. scabies uninoculation. However, the SAR pathway was induced by Trp under S. scabies inoculation. This study will provide insights into Trp-induced resistance mechanisms of potato for controlling CS, and extend the application methods of Trp as a plant resistance inducer in a way that is cheap, safe, and environmentally friendly.

Low Temperature Stress Tolerance: An Insight Into the Omics Approaches for Legume Crops

The change in climatic conditions is the major cause for decline in crop production worldwide. Decreasing crop productivity will further lead to increase in global hunger rate. Climate change results in environmental stress which has negative impact on plant-like deficiencies in growth, crop yield, permanent damage, or death if the plant remains in the stress conditions for prolonged period. Cold stress is one of the main abiotic stresses which have already affected the global crop production. Cold stress adversely affects the plants leading to necrosis, chlorosis, and growth retardation. Various physiological, biochemical, and molecular responses under cold stress have revealed that the cold resistance is more complex than perceived which involves multiple pathways. Like other crops, legumes are also affected by cold stress and therefore, an effective technique to mitigate cold-mediated damage is critical for long-term legume production. Earlier, crop improvement for any stress was challenging for scientific community as conventional breeding approaches like inter-specific or inter-generic hybridization had limited success in crop improvement. The availability of genome sequence, transcriptome, and proteome data provides in-depth sight into different complex mechanisms under cold stress. Identification of QTLs, genes, and proteins responsible for cold stress tolerance will help in improving or developing stress-tolerant legume crop. Cold stress can alter gene expression which further leads to increases in stress protecting metabolites to cope up the plant against the temperature fluctuations. Moreover, genetic engineering can help in development of new cold stress-tolerant varieties of legume crop. This paper provides a general insight into the "omics" approaches for cold stress in legume crops.

A Review of Integrative Omic Approaches for Understanding Rice Salt Response Mechanisms

Soil salinity is one of the most serious environmental challenges, posing a growing threat to agriculture across the world. Soil salinity has a significant impact on rice growth, development, and production. Hence, improving rice varieties’ resistance to salt stress is a viable solution for meeting global food demand. Adaptation to salt stress is a multifaceted process that involves interacting physiological traits, biochemical or metabolic pathways, and molecular mechanisms. The integration of multi-omics approaches contributes to a better understanding of molecular mechanisms as well as the improvement of salt-resistant and tolerant rice varieties. Firstly, we present a thorough review of current knowledge about salt stress effects on rice and mechanisms behind rice salt tolerance and salt stress signalling. This review focuses on the use of multi-omics approaches to improve next-generation rice breeding for salinity resistance and tolerance, including genomics, transcriptomics, proteomics, metabolomics and phenomics. Integrating multi-omics data effectively is critical to gaining a more comprehensive and in-depth understanding of the molecular pathways, enzyme activity and interacting networks of genes controlling salinity tolerance in rice. The key data mining strategies within the artificial intelligence to analyse big and complex data sets that will allow more accurate prediction of outcomes and modernise traditional breeding programmes and also expedite precision rice breeding such as genetic engineering and genome editing.

Recombinant Porphyromonas gingivalis W83 FimA alters immune response and metabolic gene expression in oral squamous carcinoma cells

Objectives

The Gram‐negative anaerobic rod Porphyromonas gingivalis (P. gingivalis) is regarded as a keystone pathogen in periodontitis and expresses a multitude of virulence factors iincluding fimbriae that are enabling adherence to and invasion in cells and tissues. The progression of periodontitis is a consequence of the interaction between the host immune response and periodontal pathogens. The aim of this study was to investigate the genome‐wide impact of recombinant fimbrial protein FimA from P. gingivalis W83 on the gene expression of oral squamous carcinoma cells by transcriptome analysis.

Materials and Methods

Human squamous cell carcinoma cells (SCC‐25) were stimulated for 4 and 24 h with recombinant FimA. RNA sequencing was performed and differential gene expression and enrichment were analyzed using gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and REACTOME. The results of transcriptome analysis were validated using quantitative real‐time polymerase chain reaction (PCR) with selected genes.

Results

Differential gene expression after 4 and 24 h revealed upregulation of 464 (4 h) and 179 genes (24 h) and downregulation of 69 (4 h) and 312 (24 h) genes. GO, KEGG, and REACTONE enrichment analysis identified a strong immunologic transcriptomic response signature after 4 h. After 24 h, mainly those genes were regulated, which belonged to cell metabolic pathways and replication. Real‐time PCR of selected genes belonging to immune response and signaling demonstrated strong upregulation of CCL20, TNFAIP6, CXCL8, TNFAIP3, and NFkBIA after both stimulation times.

Conclusions

These data shed light on the RNA transcriptome of human oral squamous carcinoma epithelial cells following stimulation with P. gingivalis FimA and identify a strong immunological gene expression response to this virulence factor. The data provide a base for future studies of molecular and cellular interactions between P. gingivalis and oral epithelium to elucidate basic mechanisms that may provide new prospects for periodontitis therapy and give new insights into the development and possible treatments of cancer.

Porphyromonas gingivalis W83 Membrane Components Induce Distinct Profiles of Metabolic Genes in Oral Squamous Carcinoma Cells

Periodontitis, a chronic inflammatory disease is caused by a bacterial biofilm, affecting all periodontal tissues and structures. This chronic disease seems to be associated with cancer since, in general, inflammation intensifies the risk for carcinoma development and progression. Interactions between periodontal pathogens and the host immune response induce the onset of periodontitis and are responsible for its progression, among them Porphyromonas gingivalis (P. gingivalis), a Gram-negative anaerobic rod, capable of expressing a variety of virulence factors that is considered a keystone pathogen in periodontal biofilms. The aim of this study was to investigate the genome-wide impact of P. gingivalis W83 membranes on RNA expression of oral squamous carcinoma cells by transcriptome analysis. Human squamous cell carcinoma cells (SCC-25) were infected for 4 and 24 h with extracts from P. gingivalis W83 membrane, harvested, and RNA was extracted. RNA sequencing was performed, and differential gene expression and enrichment were analyzed using GO, KEGG, and REACTOME. The results of transcriptome analysis were validated using quantitative real-time PCR with selected genes. Differential gene expression analysis resulted in the upregulation of 15 genes and downregulation of 1 gene after 4 h. After 24 h, 61 genes were upregulated and 278 downregulated. GO, KEGG, and REACTONE enrichment analysis revealed a strong metabolic transcriptomic response signature, demonstrating altered gene expressions after 4 h and 24 h that mainly belong to cell metabolic pathways and replication. Real-time PCR of selected genes belonging to immune response, signaling, and metabolism revealed upregulated expression of CCL20, CXCL8, NFkBIA, TNFAIP3, TRAF5, CYP1A1, and NOD2. This work sheds light on the RNA transcriptome of human oral squamous carcinoma cells following stimulation with P. gingivalis membranes and identifies a strong metabolic gene expression response to this periodontal pathogen. The data provide a base for future studies of molecular and cellular interactions between P. gingivalis and oral epithelium to elucidate the basic mechanisms of periodontitis and the development of cancer.

The Involvement of Long Non-coding RNA and Messenger RNA Based Molecular Networks and Pathways in the Subacute Phase of Traumatic Brain Injury in Adult Mice

Traumatic brain injury (TBI) is a complex injury with a multi-faceted recovery process. Long non-coding RNAs (lncRNAs) are demonstrated to be involved in central nervous system (CNS) disorders. However, the roles of lncRNAs in long-term neurological deficits post-TBI are poorly understood. The present study depicted the microarray’s lncRNA and messenger RNA (mRNA) profiles at 14 days in TBI mice hippocampi. LncRNA and mRNA microarray was used to identify differentially expressed genes. Quantitative real-time polymerase chain reaction (qRT-PCR) was employed to validate the microarray results. Bioinformatics analysis [including Gene Ontology (GO), the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, lncRNA-mRNA co-expression network, and lncRNA-miRNA-mRNA network] were applied to explore the underlying mechanism. A total of 264 differentially expressed lncRNAs and 232 expressed mRNAs were identified (fold change > 1.5 and P-value < 0.05). Altered genes were enriched in inflammation, immune response, blood–brain barrier, glutamatergic neurological effects, and neuroactive ligand-receptor, which may be associated with TBI-induced pathophysiologic changes in the long-term neurological deficits. The lncRNAs-mRNAs co-expression network was generated for 74 lncRNA-mRNA pairs, most of which are positive correlations. The lncRNA-miRNA-mRNA interaction network included 12 lncRNAs, 59 miRNAs, and 25 mRNAs. Numerous significantly altered lncRNAs and mRNAs in mice hippocampi were enriched in inflammation and immune response. Furthermore, these dysregulated lncRNAs and mRNAs may be promising therapeutic targets to overcome obstacles in long-term recovery following TBI.

Perspectives on Bulk-Tissue RNA Sequencing and Single-Cell RNA Sequencing for Cardiac Transcriptomics

The heart has been the center of numerous transcriptomic studies in the past decade. Even though our knowledge of the key organ in our cardiovascular system has significantly increased over the last years, it is still not fully understood yet. In recent years, extensive efforts were made to understand the genetic and transcriptomic contribution to cardiac function and failure in more detail. The advent of Next Generation Sequencing (NGS) technologies has brought many discoveries but it is unable to comprehend the finely orchestrated interactions between and within the various cell types of the heart. With the emergence of single-cell sequencing more than 10 years ago, researchers gained a valuable new tool to enable the exploration of new subpopulations of cells, cell-cell interactions, and integration of multi-omic approaches at a single-cell resolution. Despite this innovation, it is essential to make an informed choice regarding the appropriate technique for transcriptomic studies, especially when working with myocardial tissue. Here, we provide a primer for researchers interested in transcriptomics using NGS technologies.

Long RNA-Mediated Chromatin Regulation in Fission Yeast and Mammals

As part of a complex network of genome control, long regulatory RNAs exert significant influences on chromatin dynamics. Understanding how this occurs could illuminate new avenues for disease treatment and lead to new hypotheses that would advance gene regulatory research. Recent studies using the model fission yeast Schizosaccharomyces pombe (S. pombe) and powerful parallel sequencing technologies have provided many insights in this area. This review will give an overview of key findings in S. pombe that relate long RNAs to multiple levels of chromatin regulation: histone modifications, gene neighborhood regulation in cis and higher-order chromosomal ordering. Moreover, we discuss parallels recently found in mammals to help bridge the knowledge gap between the study systems.

Functional profiling of long intergenic non-coding RNAs in fission yeast

Eukaryotic genomes express numerous long intergenic non-coding RNAs (lincRNAs) that do not overlap any coding genes. Some lincRNAs function in various aspects of gene regulation, but it is not clear in general to what extent lincRNAs contribute to the information flow from genotype to phenotype. To explore this question, we systematically analysed cellular roles of lincRNAs in Schizosaccharomyces pombe. Using seamless CRISPR/Cas9-based genome editing, we deleted 141 lincRNA genes to broadly phenotype these mutants, together with 238 diverse coding-gene mutants for functional context. We applied high-throughput colony-based assays to determine mutant growth and viability in benign conditions and in response to 145 different nutrient, drug, and stress conditions. These analyses uncovered phenotypes for 47.5% of the lincRNAs and 96% of the protein-coding genes. For 110 lincRNA mutants, we also performed high-throughput microscopy and flow cytometry assays, linking 37% of these lincRNAs with cell-size and/or cell-cycle control. With all assays combined, we detected phenotypes for 84 (59.6%) of all lincRNA deletion mutants tested. For complementary functional inference, we analysed colony growth of strains ectopically overexpressing 113 lincRNA genes under 47 different conditions. Of these overexpression strains, 102 (90.3%) showed altered growth under certain conditions. Clustering analyses provided further functional clues and relationships for some of the lincRNAs. These rich phenomics datasets associate lincRNA mutants with hundreds of phenotypes, indicating that most of the lincRNAs analysed exert cellular functions in specific environmental or physiological contexts. This study provides groundwork to further dissect the roles of these lincRNAs in the relevant conditions.

The transcriptomic revolution and radiation biology

PURPOSE

This article will briefly review the origins and evolution of functional genomics, first describing the experimental technology, and then some of the approaches applied to data analysis and visualization. It will emphasize application of functional genomics to radiation biology, using examples from the author's work to illustrate several key types of analysis. It concludes with a look at non-coding RNA, alternative reading of the genome, and single-cell transcriptomics, some of the innovative areas that may help to shape future research in radiation biology and oncology.

CONCLUSIONS

Transcriptomic approaches have provided insight into many areas of radiation biology and medicine, and innovations in technology and data analysis approaches promise continued contributions to radiation science in the future.

Recommendations for pharmacotranscriptomic profiling of drug response in CNS disorders

Pharmacotranscriptomics is a still very new field of research that has just begun to flourish and promises to enable target discovery, inform biomarker and evaluate drug efficacy beyond pharmacogenomics. The aim of this review is to provide a critical overview of the biological foundations of transcriptomics, methodological approaches to transcriptomic studies, and their advantages and limitations. We present the different RNA species (rRNAs, tRNAs, mtRNAs, snRNAs, scRNAs, mRNAs, ncRNAs, LINE and SINE transcripts, circular RNAs, piRNAs, miRNAs, snoRNAs) and their potential for pharmacotranscriptomic studies as markers to predict treatment response in neurological and psychiatric disorders. We also review the accessible sources of RNA in patients peripheral blood cells (including platelets), plasma, microvesicles, exosomes, apoptotic bodies, and how those affect the integrity and relative abundances of RNAs and reflect the situation in the Central Nervous System (CNS). Finally, we discuss the suitability and indications of different techniques, such as microarrays and RNA-sequencing (RNA-Seq) techniques to understand gene expression differences or to reveal variation in expression levels of coding and non-coding genes. We conclude with some recommendations for future directions, e.g., gaps of knowledge and particular RNAs/tissues that have been overlooked.

Genome-wide chromosomal association of Upf1 is linked to Pol II transcription in Schizosaccharomyces pombe

Although the RNA helicase Upf1 has hitherto been examined mostly in relation to its cytoplasmic role in nonsense mediated mRNA decay (NMD), here we report high-throughput ChIP data indicating genome-wide association of Upf1 with active genes in Schizosaccharomyces pombe. This association is RNase sensitive, correlates with Pol II transcription and mRNA expression levels. Changes in Pol II occupancy were detected in a Upf1 deficient (upf1Δ) strain, prevalently at genes showing a high Upf1 relative to Pol II association in wild-type. Additionally, an increased Ser2 Pol II signal was detected at all highly transcribed genes examined by ChIP-qPCR. Furthermore, upf1Δ cells are hypersensitive to the transcription elongation inhibitor 6-azauracil. A significant proportion of the genes associated with Upf1 in wild-type conditions are also mis-regulated in upf1Δ. These data envisage that by operating on the nascent transcript, Upf1 might influence Pol II phosphorylation and transcription.

Biologia Futura: progress and future perspectives of long non-coding RNAs in forest trees

Forest trees are affected by climate change, anthropogenic pressure, as well as abiotic and biotic stresses. Conventional tree breeding has so far been limited to enhance overall productivity, and our understanding of the genetic basis of quantitative traits is still inadequate. Quantum leaps in next-generation sequencing technologies and bioinformatics have permitted the exploration and identification of various non-coding regions of the genome other than protein coding genes. These genomic regions produce various types of non-coding RNAs and regulate myriads of biological functions at epigenetic, transcriptional and translational levels. Recently, long non-coding RNAs (lncRNAs) which act as molecular switch have been identified to be pivotal molecules in forest trees. This review focuses on progress made in regulatory mechanisms in various developmental phases like wood formation, adventitious rooting and flowering and stress responses. It was predicted that complex regulatory interactions among lncRNA, miRNA and gene exist. LncRNAs can function as a sponge for miRNAs, reducing the suppressive effect of miRNAs on target mRNAs and perhaps adding a new layer of regulatory interactions among non-coding RNA classes in trees. Furthermore, network analysis revealed the interactions of lncRNA and genes during the expression of several important genes. The insights generated about lncRNAs in forest trees would enable improvement of economically important traits including the devastating abiotic and biotic stresses. In addition, solid understanding on the wide range of regulatory functions of lncRNAs on traits influencing biomass productivity and adaptation would aid the applications of biotechnology in genetic improvement of forest trees.

Single-Cell Analysis Using Machine Learning Techniques and Its Application to Medical Research

In recent years, the diversity of cancer cells in tumor tissues as a result of intratumor heterogeneity has attracted attention. In particular, the development of single-cell analysis technology has made a significant contribution to the field; technologies that are centered on single-cell RNA sequencing (scRNA-seq) have been reported to analyze cancer constituent cells, identify cell groups responsible for therapeutic resistance, and analyze gene signatures of resistant cell groups. However, although single-cell analysis is a powerful tool, various issues have been reported, including batch effects and transcriptional noise due to gene expression variation and mRNA degradation. To overcome these issues, machine learning techniques are currently being introduced for single-cell analysis, and promising results are being reported. In addition, machine learning has also been used in various ways for single-cell analysis, such as single-cell assay of transposase accessible chromatin sequencing (ATAC-seq), chromatin immunoprecipitation sequencing (ChIP-seq) analysis, and multi-omics analysis; thus, it contributes to a deeper understanding of the characteristics of human diseases, especially cancer, and supports clinical applications. In this review, we present a comprehensive introduction to the implementation of machine learning techniques in medical research for single-cell analysis, and discuss their usefulness and future potential.

Microbial signatures in the lower airways of mechanically ventilated COVID-19 patients associated with poor clinical outcome

Respiratory failure is associated with increased mortality in COVID-19 patients. There are no validated lower airway biomarkers to predict clinical outcome. We investigated whether bacterial respiratory infections were associated with poor clinical outcome of COVID-19 in a prospective, observational cohort of 589 critically ill adults, all of whom required mechanical ventilation. For a subset of 142 patients who underwent bronchoscopy, we quantified SARS-CoV-2 viral load, analysed the lower respiratory tract microbiome using metagenomics and metatranscriptomics and profiled the host immune response. Acquisition of a hospital-acquired respiratory pathogen was not associated with fatal outcome. Poor clinical outcome was associated with lower airway enrichment with an oral commensal (Mycoplasma salivarium). Increased SARS-CoV-2 abundance, low anti-SARS-CoV-2 antibody response and a distinct host transcriptome profile of the lower airways were most predictive of mortality. Our data provide evidence that secondary respiratory infections do not drive mortality in COVID-19 and clinical management strategies should prioritize reducing viral replication and maximizing host responses to SARS-CoV-2.

Status of diagnosis and treatment of esophageal cancer and non-coding RNA correlation research: a narrative review

OBJECTIVE

To describe and discuss the progression of the non-coding RNA as biomarkers in early esophageal cancer.

BACKGROUND

Esophageal cancer without obvious symptoms during early stages is one of the most common cancers, the current clinical treatments offer possibilities of a cure, but the survival rates and the prognoses remain poor, it is a serious threat to human life and health. Most patients are usually diagnosed during terminal stages due to low sensitivity of esophageal cancer's early detection techniques. With the development of molecular biology, an increasing number of non-coding RNAs are found to be associated with the occurrence, development, and prognosis of esophageal cancer. Some of these have begun to be used in clinics and laboratories for diagnosis, treatment, and prognosis, with the goal of reducing mortality.

METHODS

The information for this paper was collected from a variety of sources, including a search of the keynote's references, a search for texts in college libraries, and discussions with experts in the field of esophageal cancer clinical treatment.

CONCLUSIONS

Non-coding RNA does play a regulatory role in the development of esophageal cancer, which can predict the occurrence or prognosis of tumors, and become a new class of tumor markers and therapeutic targets in clinical applications. In this review, we survey the recent developments in the incidence, diagnosis, and treatment of esophageal cancer, especially with new research progresses on non-coding RNA biomarkers in detail, and discuss its potential clinical applications.

Little but Loud. The Diversity of Functions of Small Proteins and Peptides - Translational Products of Short Reading Frames

Cell functioning is tightly regulated process. For many years, research in the fields of proteomics and functional genomics has been focused on the role of proteins in cell functioning. The advances in science have led to the uncovering that short open reading frames, previously considered non-functional, serve a variety of functions. Short reading frames in polycistronic mRNAs often regulate their stability and translational efficiency of the main reading frame. The improvement of proteomic analysis methods has made it possible to identify the products of translation of short open reading frames in quantities that suggest the existence of functional role of those peptides and short proteins. Studies demonstrating their role unravel a new level of the regulation of cell functioning and its adaptation to changing conditions. This review is devoted to the analysis of functions of recently discovered peptides and short proteins.

Transcriptional Landscapes of Long Non-coding RNAs and Alternative Splicing in Pyricularia oryzae Revealed by RNA-Seq

Pyricularia oryzae causes the rice blast, which is one of the most devastating crop diseases worldwide, and is a model fungal pathogen widely used for dissecting the molecular mechanisms underlying fungal virulence/pathogenicity. Although the whole genome sequence of P. oryzae is publicly available, its current transcriptomes remain incomplete, lacking the information on non-protein coding genes and alternative splicing. Here, we performed and analyzed RNA-Seq of conidia and hyphae, resulting in the identification of 3,374 novel genes. Interestingly, the vast majority of these novel genes likely transcribed long non-coding RNAs (lncRNAs), and most of them were localized in the intergenic regions. Notably, their expressions were concomitant with the transcription of neighboring genes thereof in conidia and hyphae. In addition, 2,358 genes were found to undergo alternative splicing events. Furthermore, we exemplified that a lncRNA was important for hyphal growth likely by regulating the neighboring protein-coding gene and that alternative splicing of the transcription factor gene CON7 was required for appressorium formation. In summary, results from this study indicate that lncRNA transcripts and alternative splicing events are two important mechanisms for regulating the expression of genes important for conidiation, hyphal growth, and pathogenesis, and provide new insights into transcriptomes and gene regulation in the rice blast fungus.

Transcriptomic Analysis of Salt-Stress-Responsive Genes in Barley Roots and Leaves

Barley is characterized by a rich genetic diversity, making it an important model for studies of salinity response with great potential for crop improvement. Moreover, salt stress severely affects barley growth and development, leading to substantial yield loss. Leaf and root transcriptomes of a salt-tolerant Tunisian landrace (Boulifa) exposed to 2, 8, and 24 h salt stress were compared with pre-exposure plants to identify candidate genes and pathways underlying barley's response. Expression of 3585 genes was upregulated and 5586 downregulated in leaves, while expression of 13,200 genes was upregulated and 10,575 downregulated in roots. Regulation of gene expression was severely impacted in roots, highlighting the complexity of salt stress response mechanisms in this tissue. Functional analyses in both tissues indicated that response to salt stress is mainly achieved through sensing and signaling pathways, strong transcriptional reprograming, hormone osmolyte and ion homeostasis stabilization, increased reactive oxygen scavenging, and activation of transport and photosynthesis systems. A number of candidate genes involved in hormone and kinase signaling pathways, as well as several transcription factor families and transporters, were identified. This study provides valuable information on early salt-stress-responsive genes in roots and leaves of barley and identifies several important players in salt tolerance.

Statistical Approach of Gene Set Analysis with Quantitative Trait Loci for Crop Gene Expression Studies

Genome-wide expression study is a powerful genomic technology to quantify expression dynamics of genes in a genome. In gene expression study, gene set analysis has become the first choice to gain insights into the underlying biology of diseases or stresses in plants. It also reduces the complexity of statistical analysis and enhances the explanatory power of the obtained results from the primary downstream differential expression analysis. The gene set analysis approaches are well developed in microarrays and RNA-seq gene expression data analysis. These approaches mainly focus on analyzing the gene sets with gene ontology or pathway annotation data. However, in plant biology, such methods may not establish any formal relationship between the genotypes and the phenotypes, as most of the traits are quantitative and controlled by polygenes. The existing Quantitative Trait Loci (QTL)-based gene set analysis approaches only focus on the over-representation analysis of the selected genes while ignoring their associated gene scores. Therefore, we developed an innovative statistical approach, GSQSeq, to analyze the gene sets with trait enriched QTL data. This approach considers the associated differential expression scores of genes while analyzing the gene sets. The performance of the developed method was tested on five different crop gene expression datasets obtained from real crop gene expression studies. Our analytical results indicated that the trait-specific analysis of gene sets was more robust and successful through the proposed approach than existing techniques. Further, the developed method provides a valuable platform for integrating the gene expression data with QTL data.

Transcriptome and Small RNA Combined Sequencing Analysis of Cold Tolerance in Non-heading Chinese Cabbage

Background

Non-heading Chinese cabbage (Brassica rapa ssp. chinensis) is an important leaf vegetable grown worldwide. However, there has currently been not enough transcriptome and small RNA combined sequencing analysis of cold tolerance, which hinders further functional genomics research.

Results

In this study, 63.43 Gb of clean data was obtained from the transcriptome analysis. The clean data of each sample reached 6.99 Gb, and the basic percentage of Q30 was 93.68% and above. The clean reads of each sample were sequence aligned with the designated reference genome (Brassica rapa, IVFCAASv1), and the efficiency of the alignment varied from 81.54 to 87.24%. According to the comparison results, 1,860 new genes were discovered in Pak-choi, of which 1,613 were functionally annotated. Among them, 13 common differentially expressed genes were detected in all materials, including seven upregulated and six downregulated. At the same time, we used quantitative real-time PCR to confirm the changes of these gene expression levels. In addition, we sequenced miRNA of the same material. Our findings revealed a total of 34,182,333 small RNA reads, 88,604,604 kinds of small RNAs, among which the most common size was 24 nt. In all materials, the number of common differential miRNAs is eight. According to the corresponding relationship between miRNA and its target genes, we carried out Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis on the set of target genes on each group of differentially expressed miRNAs. Through the analysis, it is found that the distributions of candidate target genes in different materials are different. We not only used transcriptome sequencing and small RNA sequencing but also used experiments to prove the expression levels of differentially expressed genes that were obtained by sequencing. Sequencing combined with experiments proved the mechanism of some differential gene expression levels after low-temperature treatment.

Conclusion

In all, this study provides a resource for genetic and genomic research under abiotic stress in Pak-choi.

Exploiting Single-Cell Tools in Gene and Cell Therapy

Single-cell molecular tools have been developed at an incredible pace over the last five years as sequencing costs continue to drop and numerous molecular assays have been coupled to sequencing readouts. This rapid period of technological development has facilitated the delineation of individual molecular characteristics including the genome, transcriptome, epigenome, and proteome of individual cells, leading to an unprecedented resolution of the molecular networks governing complex biological systems. The immense power of single-cell molecular screens has been particularly highlighted through work in systems where cellular heterogeneity is a key feature, such as stem cell biology, immunology, and tumor cell biology. Single-cell-omics technologies have already contributed to the identification of novel disease biomarkers, cellular subsets, therapeutic targets and diagnostics, many of which would have been undetectable by bulk sequencing approaches. More recently, efforts to integrate single-cell multi-omics with single cell functional output and/or physical location have been challenging but have led to substantial advances. Perhaps most excitingly, there are emerging opportunities to reach beyond the description of static cellular states with recent advances in modulation of cells through CRISPR technology, in particular with the development of base editors which greatly raises the prospect of cell and gene therapies. In this review, we provide a brief overview of emerging single-cell technologies and discuss current developments in integrating single-cell molecular screens and performing single-cell multi-omics for clinical applications. We also discuss how single-cell molecular assays can be usefully combined with functional data to unpick the mechanism of cellular decision-making. Finally, we reflect upon the introduction of spatial transcriptomics and proteomics, its complementary role with single-cell RNA sequencing (scRNA-seq) and potential application in cellular and gene therapy.

Single-molecule, full-length transcript isoform sequencing reveals disease-associated RNA isoforms in cardiomyocytes

Alternative splicing generates differing RNA isoforms that govern phenotypic complexity of eukaryotes. Its malfunction underlies many diseases, including cancer and cardiovascular diseases. Comparative analysis of RNA isoforms at the genome-wide scale has been difficult. Here, we establish an experimental and computational pipeline that performs de novo transcript annotation and accurately quantifies transcript isoforms from cDNA sequences with a full-length isoform detection accuracy of 97.6%. We generate a searchable, quantitative human transcriptome annotation with 31,025 known and 5,740 novel transcript isoforms ( http://steinmetzlab.embl.de/iBrowser/ ). By analyzing the isoforms in the presence of RNA Binding Motif Protein 20 (RBM20) mutations associated with aggressive dilated cardiomyopathy (DCM), we identify 121 differentially expressed transcript isoforms in 107 cardiac genes. Our approach enables quantitative dissection of complex transcript architecture instead of mere identification of inclusion or exclusion of individual exons, as exemplified by the discovery of IMMT isoforms mis-spliced by RBM20 mutations. Thereby we achieve a path to direct differential expression testing independent of an existing annotation of transcript isoforms, providing more immediate biological interpretation and higher resolution transcriptome comparisons.

Application of single cell genomics to focal epilepsies: A call to action

Focal epilepsies are the largest epilepsy subtype and associated with significant morbidity. Somatic variation is a newly recognized genetic mechanism underlying a subset of focal epilepsies, but little is known about the processes through which somatic mosaicism causes seizures, the cell types carrying the pathogenic variants, or their developmental origin. Meanwhile, the inception of single cell biology has completely revolutionized the study of neurological diseases and has the potential to answer some of these key questions. Focusing on single cell genomics, transcriptomics, and epigenomics in focal epilepsy research, circumvents the averaging artifact associated with studying bulk brain tissue and offers the kind of granularity that is needed for investigating the consequences of somatic mosaicism. Here we have provided a brief overview of some of the most developed single cell techniques and the major considerations around applying them to focal epilepsy research.