RNA-Seq methods for transcriptome analysis

Comprehensive identification of RNA transcripts and construction of RNA network in chronic obstructive pulmonary disease

Background

Chronic obstructive pulmonary disease (COPD) is one of the world’s leading causes of death and a major chronic disease, highly prevalent in the aging population exposed to tobacco smoke and airborne pollutants, which calls for early and useful biomolecular predictors. Roles of noncoding RNAs in COPD have been proposed, however, not many studies have systematically investigated the crosstalk among various transcripts in this context. The construction of RNA functional networks such as lncRNA-mRNA, and circRNA-miRNA-mRNA interaction networks could therefore facilitate our understanding of RNA interactions in COPD. Here, we identified the expression of RNA transcripts in RNA sequencing from COPD patients, and the potential RNA networks were further constructed.

Methods

All fresh peripheral blood samples of three patients with COPD and three non-COPD patients were collected and examined for mRNA, miRNA, lncRNA, and circRNA expression followed by qRT-PCR validation. We also examined mRNA expression to enrich relevant biological pathways. lncRNA-mRNA coexpression network and circRNA-miRNA-mRNA network in COPD were constructed.

Results

In this study, we have comprehensively identified and analyzed the differentially expressed mRNAs, lncRNAs, miRNAs, and circRNAs in peripheral blood of COPD patients with high-throughput RNA sequencing. 282 mRNAs, 146 lncRNAs, 85 miRNAs, and 81 circRNAs were differentially expressed. GSEA analysis showed that these differentially expressed RNAs correlate with several critical biological processes such as “ncRNA metabolic process”, “ncRNA processing”, “ribosome biogenesis”, “rRNAs metabolic process”, “tRNA metabolic process” and “tRNA processing”, which might be participating in the progression of COPD. RT-qPCR with more clinical COPD samples was used for the validation of some differentially expressed RNAs, and the results were in high accordance with the RNA sequencing. Given the putative regulatory function of lncRNAs and circRNAs, we have constructed the co-expression network between lncRNA and mRNA. To demonstrate the potential interactions between circRNAs and miRNAs, we have also constructed a competing endogenous RNA (ceRNA) network of differential expression circRNA-miRNA-mRNA in COPD.

Conclusions

In this study, we have identified and analyzed the differentially expressed mRNAs, lncRNAs, miRNAs, and circRNAs, providing a systematic view of the differentially expressed RNA in the context of COPD. We have also constructed the lncRNA-mRNA co-expression network, and for the first time constructed the circRNA-miRNA-mRNA in COPD. This study reveals the RNA involvement and potential regulatory roles in COPD, and further uncovers the interactions among those RNAs, which will assist the pathological investigations of COPD and shed light on therapeutic targets exploration for COPD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12931-022-02069-8.

Paving the Way: Contributions of Big Data to Apicomplexan and Kinetoplastid Research

In the age of big data an important question is how to ensure we make the most out of the resources we generate. In this review, we discuss the major methods used in Apicomplexan and Kinetoplastid research to produce big datasets and advance our understanding of Plasmodium, Toxoplasma, Cryptosporidium, Trypanosoma and Leishmania biology. We debate the benefits and limitations of the current technologies, and propose future advancements that may be key to improving our use of these techniques. Finally, we consider the difficulties the field faces when trying to make the most of the abundance of data that has already been, and will continue to be, generated.

IL-17A deletion reduces sevoflurane-induced neurocognitive impairment in neonatal mice by inhibiting NF-κB signaling pathway

We investigated the role of IL-17A in sevoflurane-inducedneurocognitive impairment in neonatal mice. Seventy-two wild-type (WT) and 42 IL-17A knockout (KO) neonatal mice were randomly divided into WT (n = 36), IL-17A^−/− (n = 6), sevoflurane (Sev, n = 36), and IL-17A^−/− + sevoflurane (IL-17A^−/− + Sev, n = 36) groups. The latter two groups were given 3% sevoflurane for 2 h per day on postnatal days (P) 6–8. Behavioral experiments were performed on P30–36. At P37, RNA sequencing and qRT-PCR of the hippocampus was performed, neurons were detected by Nissl staining, and neuropathological changes were evaluated by HE staining. NF-κB pathway-related proteins were evaluated by western blot and immunofluorescence analyses, IL-1β and IL-6 levels were assessed by ELISA. RNA sequencing identified 131 differentially expressed genes, highlighting several enriched biological processes (chemokine activity, immune response, extracellular region, extracellular space, inflammatory response) and signaling pathways (IL-17 signaling pathway, chemokine signaling pathway, cytokine–cytokine receptor interaction, ECM–receptor interaction and influenza A). Repeated sevoflurane exposures induced long-term cognitive impairment in WT mice. The cognitive impairment was comparatively less severe in IL-17A KO mice. In addition, the increased levels of NF-κB p65, iNOS, COX-2, IL-17A, IL-6 and IL-1β, reduced neuronal numbers and neuropathological changes were ameliorated in neonatal mice in the IL-17A^−/− + Sev group compared with neonatal mice in Sev group. IL-17A deletion protects against long-term cognitive impairment induced by repeated sevoflurane exposure in neonatal mice. The underlying mechanism may relate to inhibiting NF-κB signaling pathway as well as the reducing neuroinflammation.

Transcriptome profiling of mRNAs in muscle tissue of Pinan cattle and Nanyang cattle

Mammalian muscle development is regulated by complex gene networks at the molecular level. The revelation of gene regulatory mechanisms is an important basis for the study of muscle development and molecular breeding. To analyze the excellent meat performance of Pinan cattle at the molecular level, we performed high-throughput RNA sequencing to analyze the key regulatory genes that determine the muscle quality traits in Pinan cattle (n = 3) and Nanyang cattle (n = 3). We identified 57 differentially expressed genes in muscle tissue of Pinan cattle compared to that of Nanyang cattle, including 32 upregulated and 25 downregulated genes. GO enrichment analysis showed that these genes were significantly enriched in 'molecular function', including voltage-gated ion channel activity, calcium channel activity and calcium ion binding, and KEGG pathway analysis results revealed that adrenergic signaling in cardio myocytes, cell adhesion molecules and inositol phosphate metabolism pathway were significantly enriched. We identified the reliability of RNA-Seq data through RT-qPCR. Meanwhile, we found that GSTA3, PLCB1 and ISYNA1 genes are highly expressed in muscle tissue of Pinan cattle, and these genes play important roles in PI3K/Akt, MEK1/2-ERK and p53-ISYNA1 signaling pathway. In summary, our results suggested that these differentially expressed genes may play important roles in muscle development in Pinan cattle. However, the functions and mechanism of these significantly differential expressed genes should be investigated in future studies.

Transcriptome Profiling Reveals Genes Related to Sex Determination and Differentiation in Sugarcane Borer (Chilo sacchariphagus Bojer)

Simple Summary

Chilo sacchariphagus Bojer is an important sugarcane pest globally. The identification of key genes associated with sex determination and differentiation will provide important basic information for the sterile insect technique control strategy. In this study, the comparative transcriptomic analysis of female and male adults revealed sex-biased gene expression, indicating putative genetic elements of sex determination and differentiation in this species.

Abstract

Chilo sacchariphagus Bojer is an important sugarcane pest globally. Along with genetic modification strategies, the sterile insect technique (SIT) has gained more attention as an environment-friendly method for pest control. The identification of key genes associated with sex determination and differentiation will provide important basic information for this control strategy. As such, the transcriptome sequencing of female and male adults was conducted in order to understand the sex-biased gene expression and molecular basis of sex determination and differentiation in this species. A total of 60,429 unigenes were obtained; among them, 34,847 genes were annotated. Furthermore, 11,121 deferentially expressed genes (DEGs) were identified, of which 8986 were male-biased and 2135 were female-biased genes. The male-biased genes were enriched for carbon metabolism, peptidase activity and transmembrane transport, while the female-biased genes were enriched for the cell cycle, DNA replication, and the MAPK signaling pathway. In addition, 102 genes related to sex-determination and differentiation were identified, including the protein toll, ejaculatory bulb-specific protein, fruitless, transformer-2, sex-lethal, beta-Catenin, sox, gata4, beta-tubulin, cytosol aminopeptidase, seminal fluid, and wnt4. Furthermore, transcription factors such as myb, bhlh and homeobox were also found to be potentially related to sex determination and differentiation in this species. Our data provide new insights into the genetic elements associated with sex determination and differentiation in Chilo sacchariphagus, and identified potential candidate genes to develop pest-control strategies.

Transcriptome and iTRAQ-Based Proteome Reveal the Molecular Mechanism of Intestinal Injury Induced by Weaning Ewe's Milk in Lambs

Early feeding regime has a substantial lifelong effect on lambs and weaning ewe's milk can lead to the intestinal injury of lambs. To explore the molecular regulatory mechanism of intestinal injury of lambs under weaning stress, the jejunum was conducted transcriptome and then integrated analyzed with our previous proteome data. A total of 255 upregulated genes and 285 downregulated genes were significantly identified. These genes showed low overlapping with differentially expressed proteins identified by isobaric tags for relative and absolute quantification (iTRAQ). However, according to their functions, the differentially expressed genes (DEGs) and proteins with the same expression trend were enriched for the similar Gene Ontology (GO) terms and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, such as intestinal lipid absorption, urea cycle, peroxisome proliferator-activated receptor (PPAR) signaling pathway, and ferroptosis. Furthermore, the DEGs, including FABP2, ACSL3, APOA2, APOC3, and PCK1, might play essential roles in intestinal lipid absorption and immune response through the PPAR signaling pathway and ferroptosis. This study could provide new insights into early lamb breeding at the molecular level.

Aldh1a1 and Scl25a30 in diaphragmatic dysfunction

New methods to prevent ventilator-induced diaphragmatic dysfunction (VIDD) are urgently needed, and the cellular basis of VIDD is poorly understood. This study evaluated whether transvenous phrenic nerve stimulation (PNS) could prevent VIDD in rabbits undergoing mechanical ventilation (MV) and explored whether oxidative stress-related genes might be candidate molecular markers for VIDD. Twenty-four adult male New Zealand white rabbits were allocated to control, MV, and PNS groups (n = 8 in each group). Rabbits in the MV and PNS groups underwent MV for 24 h. Intermittent bilateral transvenous PNS was performed in rabbits in the PNS group. Transdiaphragmatic pressure was recorded using balloon catheters. The diameters and cross-sectional areas (CSAs) of types I and II diaphragmatic fibers were measured using immunohistochemistry (IHC) techniques. Genes associated with VIDD were identified by RNA sequencing (RNA-seq), differentially expressed gene (DEG) analysis, and weighted gene co-expression network analysis (WGCNA). Reverse transcription polymerase chain reaction (RT-PCR), Western blotting, and IHC analyses were carried out to verify the transcriptome profile. Pdi_60Hz, Pdi_80Hz, and Pdi_100Hz were significantly higher in the PNS group than in the MV group at 12 and 24 h (P < 0.05 at both time points). The diameters and CSAs of types I (slow-twitch) and II (fast-twitch) fibers were significantly larger in the PNS group than in the MV group (P < 0.05). RNA-seq, RT-PCR, Western blotting, and IHC experiments identified two candidate genes associated with VIDD: Aldh1a1 and Scl25a30. The MV group had significantly higher mRNA and protein expressions of Aldh1a1/ALDH1A1 and significantly lower mRNA and protein expressions of Scl25a30/SCL25A30 than the control or PNS groups (P < 0.05). We have identified two candidate genes involved in the prevention of VIDD by transvenous PNS. These two key genes may provide a theoretical basis for targeted therapy against VIDD.

Transcriptome Analysis of Immune Responses and Metabolic Regulations of Chinese Soft-Shelled Turtle (Pelodiscus sinensis) against Edwardsiella tarda Infection

The Chinese soft-shelled turtle (Pelodiscus sinensis) is an important aquatic species in southern China that is threatened by many serious diseases. Edwardsiella tarda is one of the highly pathogenic bacteria that cause the white abdominal shell disease. Yet, little is known about the immune and metabolic responses of the Chinese soft-shelled turtle against E. tarda infection. In the paper, gene expression profiles in the turtle liver were obtained to study the immune responses and metabolic regulations induced by E. tarda infection using RNA sequencing. A total of 3908 differentially expressed unigenes between the experimental group and the control group were obtained by transcriptome analysis, among them, were the significantly upregulated unigenes and downregulated unigenes 2065 and 1922, respectively. Further annotation and analysis revealed that the DEGs were mainly enriched in complement and coagulation cascades, phagosome, and steroid hormone biosynthesis pathways, indicating that they were mainly associated with defense mechanisms in the turtle liver against E. tarda four days post infection. For the first time, we reported on the gene profile of anti-E. tarda response in the soft-shelled turtle, and our research might provide valuable data to support further study on anti-E. tarda defense mechanisms in turtles

DAISM-DNNXMBD: Highly accurate cell type proportion estimation with in silico data augmentation and deep neural networks

Understanding the immune cell abundance of cancer and other disease-related tissues has an important role in guiding disease treatments. Computational cell type proportion estimation methods have been previously developed to derive such information from bulk RNA sequencing data. Unfortunately, our results show that the performance of these methods can be seriously plagued by the mismatch between training data and real-world data. To tackle this issue, we propose the DAISM-DNN^XMBD (XMBD: Xiamen Big Data, a biomedical open software initiative in the National Institute for Data Science in Health and Medicine, Xiamen University, China.) (denoted as DAISM-DNN) pipeline that trains a deep neural network (DNN) with dataset-specific training data populated from a certain amount of calibrated samples using DAISM, a novel data augmentation method with an in silico mixing strategy. The evaluation results demonstrate that the DAISM-DNN pipeline outperforms other existing methods consistently and substantially for all the cell types under evaluation in real-world datasets.

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We propose a data augmentation method (DAISM) for DNN-based cell type deconvolution

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DAISM-DNN enables accurate cell type deconvolution with dataset-specific training data

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DAISM-DNN is robust to random errors in calibration samples

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Trained DAISM-DNN model is reusable across biomedical experiments following same SOP

Computational cell type deconvolution methods were developed to understand the cellular heterogeneity in disease-related tissues from bulk RNA-seq data. Due to the presence of strong batch effects, the performance of existing methods could fluctuate greatly when applied to different datasets even with the latest development in batch normalization or platform-agnostic signature designs. To tackle this issue, we proposed a DNN-based cell abundance estimation method with dataset-specific training data populated from a certain number of calibrated samples from a target dataset using DAISM, a data augmentation method using an in silico mixing strategy. DAISM-DNN enables accurate cell type proportions prediction and is robust to random errors in the ground truth cell type proportions of calibration samples. Importantly, we showed that with strict SOPs, it is possible to create a “train once, reuse many times” DAISM-DNN model for multiple biomedical experiments without the need for retraining.

Ovarian cancer-specific dysregulated genes with prognostic significance: scRNA-Seq with bulk RNA-Seq data and experimental validation

A major cause of gynecological cancer -related deaths worldwide, ovarian cancer is characterized by heterogeneity in both tumor cells and the tumor microenvironment (TME). Our study aimed to characterize tumor cell heterogeneity and the infiltration of M2 tumor-associated macrophages (TAMs) in the ovarian cancer TME by single-cell RNA-Seq (scRNA-Seq) analysis combined with bulk RNA sequencing (bulk RNA-Seq). Several highly variable genes were identified in ovarian cancer tissues, and tumor cell heterogeneity and infiltrating immune tumor cell heterogeneity were characterized in ovarian cancer cells. M2 TAMs in the TME were the predominant phenotype of TAM. Further, M2 TAM infiltration in the TME was negatively correlated with poor prognosis of ovarian cancer patients. Four M2 TAM-associated genes (SLAMF7, GNAS, TBX2-AS1, and LYPD6) correlated with the prognostic survival of ovarian cancer patients. Knockdown of SLAMF7 or GNAS mRNA repressed malignancy and cisplatin resistance of ovarian cancer cells. ScRNA-Seq combined with bulk RNA-Seq identified the same four genes associated with M2 TAMs. The prognostic risk score model based on these four genes may hold favorable predictive value for the prognosis of ovarian cancer patients.

LncRNA Biomarkers of Inflammation and Cancer

Long noncoding RNAs (lncRNAs) are promising candidates as biomarkers of inflammation and cancer. LncRNAs have several properties that make them well-suited as molecular markers of disease: (1) many lncRNAs are expressed in a tissue-specific manner, (2) distinct lncRNAs are upregulated based on different inflammatory or oncogenic stimuli, (3) lncRNAs released from cells are packaged and protected in extracellular vesicles, and (4) circulating lncRNAs in the blood are detectable using various RNA sequencing approaches. Here we focus on the potential for lncRNA biomarkers to detect inflammation and cancer, highlighting key biological, technological, and analytical considerations that will help advance the development of lncRNA-based liquid biopsies.

Small open reading frames in plant research: from prediction to functional characterization

Gene prediction is a laborious and time-consuming task. The advancement of sequencing technologies and bioinformatics tools, coupled with accelerated rate of ribosome profiling and mass spectrometry development, have made identification of small open reading frames (sORFs) (< 100 codons) in various plant genomes possible. The past 50 years have seen sORFs being isolated from many organisms. However, to date, a comprehensive sORF annotation pipeline is as yet unavailable, hence, addressed in our review. Here, we also provide current information on classification and functions of plant sORFs and their potential applications in crop improvement programs.

Genetic Aspects and Molecular Causes of Seed Longevity in Plants—A Review

Seed longevity is the most important trait related to the management of gene banks because it governs the regeneration cycle of seeds. Thus, seed longevity is a quantitative trait. Prior to the discovery of molecular markers, classical genetic studies have been performed to identify the genetic determinants of this trait. Post-2000 saw the use of DNA-based molecular markers and modern biotechnological tools, including RNA sequence (RNA-seq) analysis, to understand the genetic factors determining seed longevity. This review summarizes the most important and relevant genetic studies performed in Arabidopsis (24 reports), rice (25 reports), barley (4 reports), wheat (9 reports), maize (8 reports), soybean (10 reports), tobacco (2 reports), lettuce (1 report) and tomato (3 reports), in chronological order, after discussing some classical studies. The major genes identified and their probable roles, where available, are debated in each case. We conclude by providing information about many different collections of various crops available worldwide for advanced research on seed longevity. Finally, the use of new emerging technologies, including RNA-seq, in seed longevity research is emphasized by providing relevant examples.

TRACE-seq: A transgenic system for unbiased and non-invasive transcriptome profiling of living cells

Dynamic profiling of changes in gene expression in response to stressors in specific microenvironments without requiring cellular destruction remains challenging. Current methodologies that seek to interrogate gene expression at a molecular level require sampling of cellular transcriptome and therefore lysis of the cell, preventing serial analysis of cellular transcriptome. To address this area of unmet need, we have recently developed a technology allowing transcriptomic analysis over time without cellular destruction. Our method, TRACE-seq (TRanscriptomic Analysis Captured in Extracellular vesicles using sequencing), is characterized by a cell-type specific transgene expression. It provides data on the transcriptome inside extracellular vesicles that provides an accurate representation of stress-responsive cellular transcriptomic changes. Thus, the transcriptome of cells expressing TRACE can be followed over time without destroying the source cell, which is a powerful tool for many fields of fundamental and translational biology research.

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TRanscriptomic Analysis Captured in Extracellular vesicles using RNA-sequencing

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Excellent correlation of cellular and EV transcriptome using this method

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Accurate profiling of gene expression changes in response to stress signals

Systematic comparative analysis of strand-specific RNA-seq library preparation methods for low input samples

Despite the recent precipitous decline in the cost of genome sequencing, library preparation for RNA-seq is still laborious and expensive for applications such as high throughput screening. Limited availability of RNA generated by some experimental workflows poses an additional challenge and increases the cost of RNA library preparation. In a search for low cost, automation-compatible RNA library preparation kits that maintain strand specificity and are amenable to low input RNA quantities, we systematically tested two recent commercial technologies—Swift RNA and Swift Rapid RNA, presently offered by Integrated DNA Technologies (IDT) —alongside the Illumina TruSeq stranded mRNA, the de facto standard workflow for bulk transcriptomics. We used the Universal Human Reference RNA (UHRR) (composed of equal quantities of total RNA from 10 human cancer cell lines) to benchmark gene expression in these kits, at input quantities ranging between 10 to 500 ng. We found normalized read counts between all treatment groups to be in high agreement. Compared to the Illumina TruSeq stranded mRNA kit, both Swift RNA library kits offer shorter workflow times enabled by their patented Adaptase technology. We also found the Swift RNA kit to produce the fewest number of differentially expressed genes and pathways directly attributable to input mRNA amount.

Quercetin Regulates Calcium and Phosphorus Metabolism Through the Wnt Signaling Pathway in Broilers

This study intended to explore the effect and mechanism of different doses of dietary quercetin on calcium and phosphorus metabolism to provide an experimental basis for preventing leg disease in broilers. A total of 480 1-day-old healthy Arbor Acre broilers were randomly allotted into four groups (0, 0.02, 0.04, 0.06%) for 42 days. Compared with control, 0.06% quercetin significantly increased the unit weight and the relative weight of tibia in broilers (P < 0.05). Meanwhile, phosphorus content and bone mineral density (BMD) were significantly increased by 0.06% dietary quercetin supplementation in tibia (P < 0.05). Ash of tibia was significantly increased by 0.04 and 0.06% quercetin in broilers (P < 0.05). In addition, 0.06% quercetin significantly increased the content of serum calcium-binding protein (CB), estradiol (E₂), osteocalcin (OC), alkaline phosphatase (ALP), and calcitonin (CT) (P < 0.05); 0.04% quercetin significantly increased 1,25-dihydroxyvitamin D₃ (1,25-(OH)₂D₃) (P < 0.05) content in serum of broilers. The content of serum parathyroid (PTH) was significantly decreased by 0.02 and 0.06% quercetin (P < 0.05) in broilers. Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that the Wnt signaling pathway was a key signaling pathway of calcium and phosphorus metabolism in broilers which was significantly regulated by quercetin. The differentially expressed genes (DEGs) from transcriptome sequencing were validated with real-time quantitative PCR (RT-qPCR). In conclusion, 0.06% dietary quercetin supplementation improved calcium and phosphorus metabolism by regulating the Wnt signaling pathway in broilers.

A simple guide to de novo transcriptome assembly and annotation

A transcriptome constructed from short-read RNA sequencing (RNA-seq) is an easily attainable proxy catalog of protein-coding genes when genome assembly is unnecessary, expensive or difficult. In the absence of a sequenced genome to guide the reconstruction process, the transcriptome must be assembled de novo using only the information available in the RNA-seq reads. Subsequently, the sequences must be annotated in order to identify sequence-intrinsic and evolutionary features in them (for example, protein-coding regions). Although straightforward at first glance, de novo transcriptome assembly and annotation can quickly prove to be challenging undertakings. In addition to familiarizing themselves with the conceptual and technical intricacies of the tasks at hand and the numerous pre- and post-processing steps involved, those interested must also grapple with an overwhelmingly large choice of tools. The lack of standardized workflows, fast pace of development of new tools and techniques and paucity of authoritative literature have served to exacerbate the difficulty of the task even further. Here, we present a comprehensive overview of de novo transcriptome assembly and annotation. We discuss the procedures involved, including pre- and post-processing steps, and present a compendium of corresponding tools.

Modified Northern blot protocol for easy detection of mRNAs in total RNA using radiolabeled probes

BACKGROUND

Northern blotting is still used as a gold standard for validation of the data obtained from high-throughput whole transcriptome-based methods. However, its disadvantages of lower sensitivity, labor-intensive operation, and higher quality of RNA required limit its utilization in a routine molecular biology laboratory to monitor gene expression at RNA level. Therefore, it is necessary to optimize the traditional Northern protocol to make the technique more applicable for standard use.

RESULTS

In this paper, we report modifications and tips used to improve the traditional Northern protocol for the detection of mRNAs in total RNA. To maximize the retention of specifically bound radiolabeled probes on the blot, posthybridization washes were performed under only with moderate-stringency until the level of radioactivity retained on the filter decreased to 20~50 counts per second, rather than normally under high and low stringency sequentially for scheduled time or under only high stringent condition. Successful detection of the low-expression gene using heterologous DNA probes in 20 µg of total RNA after a two-day exposure suggested an improvement in detection sensitivity. Quantitatively controlled posthybridization washes combined with an ethidium bromide-prestaining RNA procedure to directly visualize prestained RNA bands at any time during electrophoresis or immediately after electrophoresis, which made the progress of the Northern procedure to be monitored and evaluated step by step, thereby making the experiment reliable and controllable. We also report tips used in the modified Northern protocol, including the moderate concentration of formaldehyde in the gel, the accessory capillary setup, and the staining jar placed into an enamel square tray with a lid used for hybridization. Using our modified Northern protocol, eight rounds of rehybridization could be performed on a single blot. The modification made and tips used ensured the efficient proceeding of the experiment and the resulting good performance, but without using special reagents or equipment.

CONCLUSIONS

The modified Northern protocol improved detection sensitivity and made the experiment easy, less expensive, reliable, and controllable, and can be employed in a routine molecular biology laboratory to detect low-expressed mRNAs with heterologous DNA probes in total RNA.

Transcriptome Analysis of the Toxic Effects of Amisulbrom and Isoflucypram on Zebrafish (Danio rerio) Larvae

Fungicides are frequently detected in the water bodies, however, the adverse effects of these fungicides on aquatic lives remain limited. To better understand the adverse effects of amisulbrom (AML) and isoflucypram (ISO) on embryogenesis, zebrafish embryos were exposed to two different fungicides, 0.75 μM amisulbrom (AML) and 2.5 μM isoflucypram (ISO), for 72 h. Transcriptome sequencing was employed to identify differentially expressed genes (DEGs) after AML and ISO exposure. A total of 571 and 3471 DEGs were detected between the libraries of the two fungicides-treated groups and the control, respectively. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that PPAR signaling pathway, phototransduction, ribosome and p53 signaling pathway were significantly enriched in response to both AML and ISO stress. Moreover, a number of DEGs involved in tyrosine metabolism, phagosome pathway, cell cycle pathway, extracellular matrix (ECM) receptor interaction pathway, and arginine and proline metabolism were specially enriched after exposure to AML; a number of DEGs involved in notch signaling pathway, drug metabolism, alanine, aspartate and glutamate metabolism, amino-acyl−tRNA biosynthesis, and protein processing in endoplasmic reticulum were significantly enriched after exposure to ISO. These results provide novel insights into the toxicological mechanisms underlying fish’s responses to fungicides.

Identification of a Novel Oncogenic Fusion Gene SPON1-TRIM29 in Clinical Ovarian Cancer That Promotes Cell and Tumor Growth and Enhances Chemoresistance in A2780 Cells

Gene structure alterations, such as chromosomal rearrangements that develop fusion genes, often contribute to tumorigenesis. It has been shown that the fusion genes identified in public RNA-sequencing datasets are mainly derived from intrachromosomal rearrangements. In this study, we explored fusion transcripts in clinical ovarian cancer specimens based on our RNA-sequencing data. We successfully identified an in-frame fusion transcript SPON1-TRIM29 in chromosome 11 from a recurrent tumor specimen of high-grade serous carcinoma (HGSC), which was not detected in the corresponding primary carcinoma, and validated the expression of the identical fusion transcript in another tumor from a distinct HGSC patient. Ovarian cancer A2780 cells stably expressing SPON1-TRIM29 exhibited an increase in cell growth, whereas a decrease in apoptosis was observed, even in the presence of anticancer drugs. The siRNA-mediated silencing of SPON1-TRIM29 fusion transcript substantially impaired the enhanced growth of A2780 cells expressing the chimeric gene treated with anticancer drugs. Moreover, a subcutaneous xenograft model using athymic mice indicated that SPON1-TRIM29-expressing A2780 cells rapidly generated tumors in vivo compared to control cells, whose growth was significantly repressed by the fusion-specific siRNA administration. Overall, the SPON1-TRIM29 fusion gene could be involved in carcinogenesis and chemotherapy resistance in ovarian cancer, and offers potential use as a diagnostic and therapeutic target for the disease with the fusion transcript.

Stage specific comparative transcriptomic analysis to reveal gene networks regulating iron and zinc content in pearl millet [Pennisetum glaucum (L.) R. Br.]

Pearl millet is an important staple food crop of poor people and excels all other cereals due to its unique features of resilience to adverse climatic conditions. It is rich in micronutrients like iron and zinc and amenable for focused breeding for these micronutrients along with high yield. Hence, this is a key to alleviate malnutrition and ensure nutritional security. This study was conducted to identify and validate candidate genes governing grain iron and zinc content enabling the desired modifications in the genotypes. Transcriptome sequencing using ION S5 Next Generation Sequencer generated 43.5 million sequence reads resulting in 83,721 transcripts with N₅₀ of 597 bp and 84.35% of transcripts matched with the pearl millet genome assembly. The genotypes having high iron and zinc showed differential gene expression during different stages. Of which, 155 were up-regulated and 251 were down-regulated while during flowering stage and milking stage 349 and 378 transcripts were differentially expressed, respectively. Gene annotation and GO term showed the presence of transcripts involved in metabolic activities associated with uptake and transport of iron and zinc. Information generated will help in gaining insights into iron and zinc metabolism and develop genotypes with high yield, grain iron and zinc content.

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.

NTRK insights: best practices for pathologists

Since the discovery of an oncogenic tropomyosin-receptor kinase (TRK) fusion protein in the early 1980s, our understanding of neurotrophic tropomyosin-receptor kinase (NTRK) fusions, their unique patterns of frequency in different tumor types, and methods to detect them have grown in scope and depth. Identification of these molecular alterations in the management of patients with cancer has become increasingly important with the emergence of histology-agnostic, US Food and Drug Administration-approved, effective TRK protein inhibitors. Herein, we review the biology of TRK in normal and malignant tissues, as well as the prevalence and enrichment patterns of these fusions across tumor types. Testing methods currently used to identify NTRK1-3 fusions will be reviewed in detail, with attention to newer assays including RNA-based next-generation sequencing. Recently proposed algorithms for NTRK fusion testing will be compared, and practical insights provided on how testing can best be implemented and communicated within the multidisciplinary healthcare team.

Prostate-specific membrane antigen modulates the progression of prostate cancer by regulating the synthesis of arginine and proline and the expression of androgen receptors and Fos proto-oncogenes

The expression of prostate-specific membrane antigen (PSMA) is strikingly upregulated during oncogenesis and prostate cancer (PCa) progression, but the functions of this antigen in PCa remain unclear. Here, we constructed PSMA-knockdown LNCaP and 22rv1 cell lines and performed metabonomic and transcriptomic analyses to determine the effects of PSMA on PCa metabolism and transcription. The metabolism of arginine and proline was detected using specific kits. The mRNA and protein expression levels of the identified differentially expressed genes were quantified by RT-qPCR and Western blotting. The proliferation of each cell line was evaluated through CCK-8, EdU and colony formation assays. The migration and invasion abilities of each cell line were detected using wound healing and transwell assays, respectively. PSMA knockdown led to metabolic disorder and abnormal transcription in PCa and resulted in inhibition of the proliferation and metastasis of PCa cells in vitro and in vivo. The depletion of PSMA also promoted the biosynthesis of arginine and proline, inhibited the expression of AR and PSA, and induced the expression of c-Fos and FosB. PSMA plays an important role in the metabolism, proliferation and metastasis of human PCa and may be a promising therapeutic target.

Recent advances in neuropeptide-related omics and gene editing: Spotlight on NPY and somatostatin and their roles in growth and food intake of fish

Feeding and growth are two closely related and important physiological processes in living organisms. Studies in mammals have provided us with a series of characterizations of neuropeptides and their receptors as well as their roles in appetite control and growth. The central nervous system, especially the hypothalamus, plays an important role in the regulation of appetite. Based on their role in the regulation of feeding, neuropeptides can be classified as orexigenic peptide and anorexigenic peptide. To date, the regulation mechanism of neuropeptide on feeding and growth has been explored mainly from mammalian models, however, as a lower and diverse vertebrate, little is known in fish regarding the knowledge of regulatory roles of neuropeptides and their receptors. In recent years, the development of omics and gene editing technology has accelerated the speed and depth of research on neuropeptides and their receptors. These powerful techniques and tools allow a more precise and comprehensive perspective to explore the functional mechanisms of neuropeptides. This paper reviews the recent advance of omics and gene editing technologies in neuropeptides and receptors and their progresses in the regulation of feeding and growth of fish. The purpose of this review is to contribute to a comparative understanding of the functional mechanisms of neuropeptides in non-mammalians, especially fish.

Advances in understanding of the innate immune response to human norovirus infection using organoid models

Norovirus is the leading cause of epidemic and endemic acute gastroenteritis worldwide and the most frequent cause of foodborne illness in the United States. There is no specific treatment for norovirus infections and therapeutic interventions are based on alleviating symptoms and limiting viral transmission. The immune response to norovirus is not completely understood and mechanistic studies have been hindered by lack of a robust cell culture system. In recent years, the human intestinal enteroid/human intestinal organoid system (HIE/HIO) has enabled successful human norovirus replication. Cells derived from HIE have also successfully been subjected to genetic manipulation using viral vectors as well as CRISPR/Cas9 technology, thereby allowing studies to identify antiviral signaling pathways important in controlling norovirus infection. RNA sequencing using HIE cells has been used to investigate the transcriptional landscape during norovirus infection and to identify antiviral genes important in infection. Other cell culture platforms such as the microfluidics-based gut-on-chip technology in combination with the HIE/HIO system also have the potential to address fundamental questions on innate immunity to human norovirus. In this review, we highlight the recent advances in understanding the innate immune response to human norovirus infections in the HIE system, including the application of advanced molecular technologies that have become available in recent years such as the CRISPR/Cas9 and RNA sequencing, as well as the potential application of single cell transcriptomics, viral proteomics, and gut-on-a-chip technology to further elucidate innate immunity to norovirus.

Transcriptome analysis of the early stage ifnlr1-mutant zebrafish indicates the immune response to auditory dysfunction

BACKGROUND

IFNLR1 has been recently identified to be related to autosomal dominant nonsyndromic sensorineural hearing loss (ADNSHL). It is reported to be expressed in the inner ear of mice and the lateral line of zebrafish. However, it remains unclear how defects in this gene lead to hearing loss.

OBJECTIVES

To elucidate the global gene expression changes in zebrafish when the expression of ifnlr1 is downregulated.

METHODS

Transcriptome analysis was performed on ifnlr1 morpholino knockdown zebrafish and the control zebrafish using RNA-seq technology.

RESULTS

The results show that 262 differentially expressed genes (DEGs) were up-regulated while 146 DEGs were down-regulated in the E4I4-Mo zebrafish larvae compared to the control-Mo. Six pathways were significantly enriched, including steroid biosynthesis pathway, adipocytokine signaling pathway, cytokine-cytokine receptor interaction pathway, p53 signaling pathway, AGE-RAGE signaling pathway in diabetic complications, and terpenoid backbone biosynthesis pathway. Among them, three pathways (steroid biosynthesis pathway, cytokine-cytokine receptor interaction pathway and p53 signaling pathway) are immune-associated.

CONCLUSIONS

The transcriptome analysis results contribute to the groundwork for future research on the pathogenesis of IFNLR1-associated hearing loss.

Small Molecule Drugs Targeting Non-Coding RNAs as Treatments for Alzheimer's Disease and Related Dementias

Despite the enormous burden of Alzheimer's disease and related dementias (ADRD) on patients, caregivers, and society, only a few treatments with limited efficacy are currently available. While drug development conventionally focuses on disease-associated proteins, RNA has recently been shown to be druggable for therapeutic purposes as well. Approximately 70% of the human genome is transcribed into non-protein-coding RNAs (ncRNAs) such as microRNAs, long ncRNAs, and circular RNAs, which can adopt diverse structures and cellular functions. Many ncRNAs are specifically enriched in the central nervous system, and their dysregulation is implicated in ADRD pathogenesis, making them attractive therapeutic targets. In this review, we first detail why targeting ncRNAs with small molecules is a promising therapeutic strategy for ADRD. We then outline the process from discovery to validation of small molecules targeting ncRNAs in preclinical studies, with special emphasis on primary high-throughput screens for identifying lead compounds. Screening strategies for specific ncRNAs will also be included as examples. Key challenges-including selecting appropriate ncRNA targets, lack of specificity of small molecules, and general low success rate of neurological drugs and how they may be overcome-will be discussed throughout the review.

Improving the quality of barley transcriptome de novo assembling by using a hybrid approach for lines with varying spike and stem coloration

De novo transcriptome assembly is an important stage of RNA-seq data computational analysis. It allows the researchers to obtain the sequences of transcripts presented in the biological sample of interest. The availability of accurate and complete transcriptome sequence of the organism of interest is, in turn, an indispensable condition for further analysis of RNA-seq data. Through years of transcriptomic research, the bioinformatics community has developed a number of assembler programs for transcriptome reconstruction from short reads of RNA-seq libraries. Different assemblers makes it possible to conduct a de novo transcriptome reconstruction and a genome-guided reconstruction. The majority of the assemblers working with RNA-seq data are based on the De Bruijn graph method of sequence reconstruction. However, specif ics of their procedures can vary drastically, as do their results. A number of authors recommend a hybrid approach to transcriptome reconstruction based on combining the results of several assemblers in order to achieve a better transcriptome assembly. The advantage of this approach has been demonstrated in a number of studies, with RNA-seq experiments conducted on the Illumina platform. In this paper, we propose a hybrid approach for creating a transcriptome assembly of the barley Hordeum vulgare isogenic line Bowman and two nearly isogenic lines contrasting in spike pigmentation, based on the results of sequencing on the IonTorrent platform. This approach implements several de novo assemblers: Trinity, Trans-ABySS and rnaSPAdes. Several assembly metrics were examined: the percentage of reference transcripts observed in the assemblies, the percentage of RNA-seq reads involved, and BUSCO scores. It was shown that, based on the summation of these metrics, transcriptome meta-assembly surpasses individual transcriptome assemblies it consists of.

Possible Role of Accessory Proteins in the Viral Replication for the 20I/501Y.V1 (B.1.1.7) SARS CoV-2 Variant

The emergence of new severe acute respiratory syndrome coronavirus-2 (SARS CoV-2) has been a global concern. The B.1.1.7 variant of SARS CoV-2 is reported to cause higher transmission. The study investigates the replication cycle and transcriptional pattern of the B.1.1.7 to hypothesis the possible role of different genes in viral replication. It was observed that the B.1.1.7 variant required a longer maturation time. The transcriptional response demonstrated higher expression of ORF6 and ORF8 compared to nucleocapsid transcript till the eclipse period which might influence higher viral replication. The number of infectious viruses titer is higher in the B.1.1.7, despite a lesser copy number than B.1, indicating higher transmissibility. The experimental evidence published linked ORF6 and ORF8 to play important role in replication and we also observed their higher expression. This leads us to hypothesis the possible role of ORF6 and ORF8 in B.1.1.7 higher replication which causes higher transmission.

Application of third-generation sequencing in cancer research

In the past several years, nanopore sequencing technology from Oxford Nanopore Technologies (ONT) and single-molecule real-time (SMRT) sequencing technology from Pacific BioSciences (PacBio) have become available to researchers and are currently being tested for cancer research. These methods offer many advantages over most widely used high-throughput short-read sequencing approaches and allow the comprehensive analysis of transcriptomes by identifying full-length splice isoforms and several other posttranscriptional events. In addition, these platforms enable structural variation characterization at a previously unparalleled resolution and direct detection of epigenetic marks in native DNA and RNA. Here, we present a comprehensive summary of important applications of these technologies in cancer research, including the identification of complex structure variants, alternatively spliced isoforms, fusion transcript events, and exogenous RNA. Furthermore, we discuss the impact of the newly developed nanopore direct RNA sequencing (RNA-Seq) approach in advancing epitranscriptome research in cancer. Although the unique challenges still present for these new single-molecule long-read methods, they will unravel many aspects of cancer genome complexity in unprecedented ways and present an encouraging outlook for continued application in an increasing number of different cancer research settings.

Omics-Facilitated Crop Improvement for Climate Resilience and Superior Nutritive Value

Novel crop improvement approaches, including those that facilitate for the exploitation of crop wild relatives and underutilized species harboring the much-needed natural allelic variation are indispensable if we are to develop climate-smart crops with enhanced abiotic and biotic stress tolerance, higher nutritive value, and superior traits of agronomic importance. Top among these approaches are the "omics" technologies, including genomics, transcriptomics, proteomics, metabolomics, phenomics, and their integration, whose deployment has been vital in revealing several key genes, proteins and metabolic pathways underlying numerous traits of agronomic importance, and aiding marker-assisted breeding in major crop species. Here, citing several relevant examples, we appraise our understanding on the recent developments in omics technologies and how they are driving our quest to breed climate resilient crops. Large-scale genome resequencing, pan-genomes and genome-wide association studies are aiding the identification and analysis of species-level genome variations, whilst RNA-sequencing driven transcriptomics has provided unprecedented opportunities for conducting crop abiotic and biotic stress response studies. Meanwhile, single cell transcriptomics is slowly becoming an indispensable tool for decoding cell-specific stress responses, although several technical and experimental design challenges still need to be resolved. Additionally, the refinement of the conventional techniques and advent of modern, high-resolution proteomics technologies necessitated a gradual shift from the general descriptive studies of plant protein abundances to large scale analysis of protein-metabolite interactions. Especially, metabolomics is currently receiving special attention, owing to the role metabolites play as metabolic intermediates and close links to the phenotypic expression. Further, high throughput phenomics applications are driving the targeting of new research domains such as root system architecture analysis, and exploration of plant root-associated microbes for improved crop health and climate resilience. Overall, coupling these multi-omics technologies to modern plant breeding and genetic engineering methods ensures an all-encompassing approach to developing nutritionally-rich and climate-smart crops whose productivity can sustainably and sufficiently meet the current and future food, nutrition and energy demands.

Comparative transcriptome analysis of thiamethoxam susceptible and resistant Asian citrus psyllid, Diaphorina citri (Hemiptera: Liviidae), using RNA-sequencing

Asian citrus psyllid, Diaphorina citri Kuwayama (Hemiptera: Liviidae), transmits the causal pathogen of huanglongbing and is a global pest of citrus. D. citri populations exhibit resistance to multiple insecticide modes of action in areas where these chemicals have been overused. We performed genome-wide transcriptional analysis for two field populations of D. citri (Wauchula and Lake Alfred, Florida, USA) that exhibit 1300-fold resistance to the neonicotinoid insecticide, thiamethoxam, and compared it to that of susceptible psyllids collected from the same area and without imposed selection. The Lake Alfred population responded to insecticide resistance by up-regulation of 240 genes and down-regulation of 148 others. The Wauchula population exhibited similar patterns to the Lake Alfred population with up-regulation of 253 genes and down-regulation of 115 others. Gene Ontology annotation associated with cellular processes, cell, and catalytic activity were assigned to differentially expressed genes (DEGs). The DEGs from Lake Alfred and Wauchula populations were mapped to Kyoto Encyclopedia of Gene and Genomes pathways and implicated enrichment of metabolic pathways, oxidative phosphorylation, extracellular matrix-receptor interaction, terpenoid backbone biosynthesis, and insect hormone biosynthesis in the resistant populations. Up-regulation of 60s ribosomal proteins, UDP-gluscoyltransferases, cytochrome c oxidases, and CYP and ABC transporters among thiamethoxam-resistant D. citri implicates a broad array of novel and conventionally understood resistance mechanisms.

Phospho-RNA sequencing with circAID-p-seq

Most RNA footprinting approaches that require ribonuclease cleavage generate RNA fragments bearing a phosphate or cyclic phosphate group at their 3′ end. Unfortunately, current library preparation protocols rely only on a 3′ hydroxyl group for adaptor ligation or poly-A tailing. Here, we developed circAID-p-seq, a PCR-free library preparation for selective 3′ phospho-RNA sequencing. As a proof of concept, we applied circAID-p-seq to ribosome profiling, which is based on sequencing of RNA fragments protected by ribosomes after endonuclease digestion. CircAID-p-seq, combined with the dedicated computational pipeline circAidMe, facilitates accurate, fast and highly efficient sequencing of phospho-RNA fragments from eukaryotic cells and tissues. We used circAID-p-seq to portray ribosome occupancy in transcripts, providing a versatile and PCR-free strategy to possibly unravel any endogenous 3′-phospho RNA molecules.

RNA sequencing reveals induction of specific renal inflammatory pathways in a rat model of malignant hypertension

In malignant hypertension, far more severe kidney injury occurs than in the "benign" form of the disease. The role of high blood pressure and the renin-angiotensin-aldosterone system is well recognized, but the pathogenesis of the renal injury of malignant hypertension (MH) remains incompletely understood. Using the rat model of two-kidney, one-clip renovascular hypertension in which some but not all animals develop MH, we performed a transcriptomic analysis of gene expression by RNA sequencing to identify transcriptional changes in the kidney cortex specific for MH. Differential gene expression was assessed in three groups: MH, non-malignant hypertension (NMH), and normotensive, sham-operated controls. To distinguish MH from NMH, we considered two factors: weight loss and typical renovascular lesions. Mean blood pressure measured intraarterially was elevated in MH (220 ± 6.5 mmHg) as well as in NMH (192 ± 6.4 mmHg), compared to controls (119 ± 1.7 mmHg, p < 0.05). Eight hundred eighty-six genes were exclusively regulated in MH only. Principal component analysis revealed a separated clustering of the three groups. The data pointed to an upregulation of many inflammatory mechanisms in MH including pathways which previously attracted relatively little attention in the setting of hypertensive kidney injury: Transcripts from all three complement activation pathways were upregulated in MH compared to NMH but not in NMH compared with controls; immunohistochemistry confirmed complement deposition in MH exclusively. The expression of chemokines attracting neutrophil granulocytes (CXCL6) and infiltration of myeloperoxidase-positive cells were increased only in MH rats. The data suggest that these pathways, especially complement deposition, may contribute to kidney injury under MH. KEY MESSAGES: The most severe hypertension-induced kidney injury occurs in malignant hypertension. In a rat model of malignant hypertension, we assessed transcriptional responses in the kidney exposed to high blood pressure. A broad stimulation of inflammatory mechanisms was observed, but a few specific pathways were activated only in the malignant form of the disease, notably activation of the complement cascades. Complement inhibitors may alleviate the thrombotic microangiopathy of malignant hypertension even in the absence of primary complement abnormalities.

Perspective of the GEMSTONE Consortium on Current and Future Approaches to Functional Validation for Skeletal Genetic Disease Using Cellular, Molecular and Animal-Modeling Techniques

The availability of large human datasets for genome-wide association studies (GWAS) and the advancement of sequencing technologies have boosted the identification of genetic variants in complex and rare diseases in the skeletal field. Yet, interpreting results from human association studies remains a challenge. To bridge the gap between genetic association and causality, a systematic functional investigation is necessary. Multiple unknowns exist for putative causal genes, including cellular localization of the molecular function. Intermediate traits ("endophenotypes"), e.g. molecular quantitative trait loci (molQTLs), are needed to identify mechanisms of underlying associations. Furthermore, index variants often reside in non-coding regions of the genome, therefore challenging for interpretation. Knowledge of non-coding variance (e.g. ncRNAs), repetitive sequences, and regulatory interactions between enhancers and their target genes is central for understanding causal genes in skeletal conditions. Animal models with deep skeletal phenotyping and cell culture models have already facilitated fine mapping of some association signals, elucidated gene mechanisms, and revealed disease-relevant biology. However, to accelerate research towards bridging the current gap between association and causality in skeletal diseases, alternative in vivo platforms need to be used and developed in parallel with the current -omics and traditional in vivo resources. Therefore, we argue that as a field we need to establish resource-sharing standards to collectively address complex research questions. These standards will promote data integration from various -omics technologies and functional dissection of human complex traits. In this mission statement, we review the current available resources and as a group propose a consensus to facilitate resource sharing using existing and future resources. Such coordination efforts will maximize the acquisition of knowledge from different approaches and thus reduce redundancy and duplication of resources. These measures will help to understand the pathogenesis of osteoporosis and other skeletal diseases towards defining new and more efficient therapeutic targets.

Transcriptome Analysis of Neuroendocrine Regulation of Ovine Hypothalamus-Pituitary-Ovary Axis during Ovine Anestrus and the Breeding Season

Most sheep are seasonal estrus, and they breed in autumn when the days get shorter. Seasonal estrus is an important factor that affects the productivity and fertility of sheep. The key point to solve this problem is to explore the regulation mechanism of estrus in sheep. Therefore, in this study, transcriptomic sequencing technology was used to identify differentially expressed mRNAs in the hypothalamus, pituitary and ovary of Small Tail Han sheep (year-round estrus) and tan sheep (seasonal estrus) among luteal, proestrus and estrus stages. There were 256,923,304,156 mRNAs being identified in the hypothalamus, pituitary and ovary, respectively. Functional analysis showed that the photosensor, leucine and isoleucine biosynthesis pathways were enriched significantly. It is speculated that photoperiod may initiate estrus by stimulating the corresponding pathways in hypothalamus. ODC1, PRLH, CRYBB2, SMAD5, OPN1SW, TPH1 are believed to be key genes involved in the estrogen process. In conclusion, this study expanded the database of indigenous sheep breeds, and also provided new candidate genes for future genetic and molecular studies on the seasonal estrus trait in sheep.

A Novel Calibration Step in Gene Co-Expression Network Construction

High-throughput technologies such as DNA microarrays and RNA-sequencing are used to measure the expression levels of large numbers of genes simultaneously. To support the extraction of biological knowledge, individual gene expression levels are transformed to Gene Co-expression Networks (GCNs). In a GCN, nodes correspond to genes, and the weight of the connection between two nodes is a measure of similarity in the expression behavior of the two genes. In general, GCN construction and analysis includes three steps; 1) calculating a similarity value for each pair of genes 2) using these similarity values to construct a fully connected weighted network 3) finding clusters of genes in the network, commonly called modules. The specific implementation of these three steps can significantly impact the final output and the downstream biological analysis. GCN construction is a well-studied topic. Existing algorithms rely on relatively simple statistical and mathematical tools to implement these steps. Currently, software package WGCNA appears to be the most widely accepted standard. We hypothesize that the raw features provided by sequencing data can be leveraged to extract modules of higher quality. A novel preprocessing step of the gene expression data set is introduced that in effect calibrates the expression levels of individual genes, before computing pairwise similarities. Further, the similarity is computed as an inner-product of positive vectors. In experiments, this provides a significant improvement over WGCNA, as measured by aggregate p-values of the gene ontology term enrichment of the computed modules.

cyPhyRNA-seq: a genome-scale RNA-seq method to detect active self-cleaving ribozymes by capturing RNAs with 2',3' cyclic phosphates and 5' hydroxyl ends

Self-cleaving ribozymes are catalytically active RNAs that cleave themselves into a 5′-fragment with a 2′,3′-cyclic phosphate and a 3′-fragment with a 5′-hydroxyl. They are widely applied for the construction of synthetic RNA devices and RNA-based therapeutics. However, the targeted discovery of self-cleaving ribozymes remains a major challenge. We developed a transcriptome-wide method, called cyPhyRNA-seq, to screen for ribozyme cleavage fragments in total RNA extract. This approach employs the specific ligation-based capture of ribozyme 5′-fragments using a variant of the Arabidopsis thaliana tRNA ligase we engineered. To capture ribozyme 3′-fragments, they are enriched from total RNA by enzymatic treatments. We optimized and enhanced the individual steps of cyPhyRNA-seq in vitro and in spike-in experiments. Then, we applied cyPhyRNA-seq to total RNA isolated from the bacterium Desulfovibrio vulgaris and detected self-cleavage of the three predicted type II hammerhead ribozymes, whose activity had not been examined to date. cyPhyRNA-seq can be used for the global analysis of active self-cleaving ribozymes with the advantage to capture both ribozyme cleavage fragments from total RNA. Especially in organisms harbouring many self-cleaving RNAs, cyPhyRNA-seq facilitates the investigation of cleavage activity. Moreover, this method has the potential to be used to discover novel self-cleaving ribozymes in different organisms.

Development of a bioinformatics platform for analysis of quantitative transcriptomics and proteomics data: the OMnalysis

BACKGROUND

In the past decade, RNA sequencing and mass spectrometry based quantitative approaches are being used commonly to identify the differentially expressed biomarkers in different biological conditions. Data generated from these approaches come in different sizes (e.g., count matrix, normalized list of differentially expressed biomarkers, etc.) and shapes (e.g., sequences, spectral data, etc.). The list of differentially expressed biomarkers is used for functional interpretation and retrieve biological meaning, however, it requires moderate computational skills. Thus, researchers with no programming expertise find difficulty in data interpretation. Several bioinformatics tools are available to analyze such data; however, they are less flexible for performing the multiple steps of visualization and functional interpretation.

IMPLEMENTATION

We developed an easy-to-use Shiny based web application (named as OMnalysis) that provides users with a single platform to analyze and visualize the differentially expressed data. The OMnalysis accepts the data in tabular form from edgeR, DESeq2, MaxQuant Perseus, R packages, and other similar software, which typically contains the list of differentially expressed genes or proteins, log of the fold change, log of the count per million, the P value, q-value, etc. The key features of the OMnalysis are multiple image type visualization and their dimension customization options, seven multiple hypothesis testing correction methods to get more significant gene ontology, network topology-based pathway analysis, and multiple databases support (KEGG, Reactome, PANTHER, biocarta, NCI-Nature Pathway Interaction Database PharmGKB and STRINGdb) for extensive pathway enrichment analysis. OMnalysis also fetches the literature information from PubMed to provide supportive evidence to the biomarkers identified in the analysis. In a nutshell, we present the OMnalysis as a well-organized user interface, supported by peer-reviewed R packages with updated databases for quick interpretation of the differential transcriptomics and proteomics data to biological meaning.

AVAILABILITY

The OMnalysis codes are entirely written in R language and freely available at https://github.com/Punit201016/OMnalysis. OMnalysis can also be accessed from - http://lbmi.uvlf.sk/omnalysis.html. OMnalysis is hosted on a Shiny server at https://omnalysis.shinyapps.io/OMnalysis/. The minimum system requirements are: 4 gigabytes of RAM, i3 processor (or equivalent). It is compatible with any operating system (windows, Linux or Mac). The OMnalysis is heavily tested on Chrome web browsers; thus, Chrome is the preferred browser. OMnalysis works on Firefox and Safari.

The Single-Cell Sequencing: A Dazzling Light Shining on the Dark Corner of Cancer

Tumorigenesis refers to the process of clonal dysplasia that occurs due to the collapse of normal growth regulation in cells caused by the action of various carcinogenic factors. These “successful” tumor cells pass on the genetic templates to their generations in evolutionary terms, but they also constantly adapt to ever-changing host environments. A unique peculiarity known as intratumor heterogeneity (ITH) is extensively involved in tumor development, metastasis, chemoresistance, and immune escape. An understanding of ITH is urgently required to identify the diversity and complexity of the tumor microenvironment (TME), but achieving this understanding has been a challenge. Single-cell sequencing (SCS) is a powerful tool that can gauge the distribution of genomic sequences in a single cell and the genetic variability among tumor cells, which can improve the understanding of ITH. SCS provides fundamental ideas about existing diversity in specific TMEs, thus improving cancer diagnosis and prognosis prediction, as well as improving the monitoring of therapeutic response. Herein, we will discuss advances in SCS and review SCS application in tumors based on current evidence.

Transcriptome and MicroRNAs Profiling Analysis of Huh7.5.1 Cells in Response to Hepatitis C Virus Infection

Background: There is a great need for further study on the mechanism of HCV infection or its pathopoiesis mechanism. Therefore, an HCV infection model was used to analyze the mechanisms of transcriptional and post-transcriptional regulation of gene expression. Methods: The detections of transcriptome and microRNAs expressions in Huh7.5.1 cells infected with JFH-1 were conducted with next-generation sequencing. Moreover, bioinformatics data were obtained. Results: There were 21,827,299, and 42,588,251 reads qualified Illumina read pairs obtained from JFH-1-infected (HCV) and non-infected (blank) Huh7.5.1 cells, respectively. Moreover, 678 and 1,041 mRNAs data with a length of 101 bp from HCV and blank Huh7.5.1 cells cDNA sequence were generated, respectively. The results of comparative transcriptome sequencing analysis declared 460 differentially expressed mRNAs in HCV-infected cells, including 152 upregulated mRNAs and 308 downregulated mRNAs (HCV vs. blank). Gene Ontology (GO) and KEGG pathway enrichment analyses indicated the involved pathways, such as MAPK, p53, and PI3K/Akt signaling pathways, as well as oocyte meiosis and pathways in cancer. Conclusions: Our work confirmed the transcriptome and microRNA data profiling from the cell model of HCV infection with JFH-1 using next-generation sequencing (NGS). Furthermore, the gene expression and regulation information or signaling pathways associated with the pathopoiesis mechanism of HCV infection were identified.

Toward Integrated Multi-Omics Intervention: Rice Trait Improvement and Stress Management

Rice (Oryza sativa) is an imperative staple crop for nearly half of the world's population. Challenging environmental conditions encompassing abiotic and biotic stresses negatively impact the quality and yield of rice. To assure food supply for the unprecedented ever-growing world population, the improvement of rice as a crop is of utmost importance. In this era, "omics" techniques have been comprehensively utilized to decipher the regulatory mechanisms and cellular intricacies in rice. Advancements in omics technologies have provided a strong platform for the reliable exploration of genetic resources involved in rice trait development. Omics disciplines like genomics, transcriptomics, proteomics, and metabolomics have significantly contributed toward the achievement of desired improvements in rice under optimal and stressful environments. The present review recapitulates the basic and applied multi-omics technologies in providing new orchestration toward the improvement of rice desirable traits. The article also provides a catalog of current scenario of omics applications in comprehending this imperative crop in relation to yield enhancement and various environmental stresses. Further, the appropriate databases in the field of data science to analyze big data, and retrieve relevant information vis-à-vis rice trait improvement and stress management are described.

ZmbHLH124 identified in maize recombinant inbred lines contributes to drought tolerance in crops

Due to climate change, drought has become a severe abiotic stress that affects the global production of all crops. Elucidation of the complex physiological mechanisms underlying drought tolerance in crops will support the cultivation of new drought-tolerant crop varieties. Here, two drought-tolerant lines, RIL70 and RIL73, and two drought-sensitive lines, RIL44 and RIL93, from recombinant inbred lines (RIL) generated from maize drought-tolerant line PH4CV and drought-sensitive line F9721, were selected for a comparative RNA-seq study. Through transcriptome analyses, we found that gene expression differences existed between drought-tolerant and -sensitive lines, but also differences between the drought-tolerant lines, RIL70 and RIL73. ZmbHLH124 in RIL73, named as ZmbHLH124T-ORG which origins from PH4CV and encodes a bHLH type transcription factor, was specifically up-regulated during drought stress. In addition, we identified a substitution in ZmbHLH124 that produced an early stop codon in sensitive lines (ZmbHLH124S-ORG ). Overexpression of ZmbHLH124T-ORG , but not ZmbHLH124S-ORG , in maize and rice enhanced plant drought tolerance and up-regulated the expression of drought-responsive genes. Moreover, we found that ZmbHLH124T-ORG could directly bind the cis-acting elements in ZmDREB2A promoter to enhance its expression. Taken together, this work identified a valuable genetic locus and provided a new strategy for breeding drought-tolerant crops.

Bias-invariant RNA-sequencing metadata annotation

BACKGROUND

Recent technological advances have resulted in an unprecedented increase in publicly available biomedical data, yet the reuse of the data is often precluded by experimental bias and a lack of annotation depth and consistency. Missing annotations makes it impossible for researchers to find datasets specific to their needs.

FINDINGS

Here, we investigate RNA-sequencing metadata prediction based on gene expression values. We present a deep-learning-based domain adaptation algorithm for the automatic annotation of RNA-sequencing metadata. We show, in multiple experiments, that our model is better at integrating heterogeneous training data compared with existing linear regression-based approaches, resulting in improved tissue type classification. By using a model architecture similar to Siamese networks, the algorithm can learn biases from datasets with few samples.

CONCLUSION

Using our novel domain adaptation approach, we achieved metadata annotation accuracies up to 15.7% better than a previously published method. Using the best model, we provide a list of >10,000 novel tissue and sex label annotations for 8,495 unique SRA samples. Our approach has the potential to revive idle datasets by automated annotation making them more searchable.

Pearl Millet: A Climate-Resilient Nutricereal for Mitigating Hidden Hunger and Provide Nutritional Security

Pearl millet [Pennisetum glaucum (L.) R. Br.] is the sixth most important cereal crop after rice, wheat, maize, barley and sorghum. It is widely grown on 30 million ha in the arid and semi-arid tropical regions of Asia and Africa, accounting for almost half of the global millet production. Climate change affects crop production by directly influencing biophysical factors such as plant and animal growth along with the various areas associated with food processing and distribution. Assessment of the effects of global climate changes on agriculture can be helpful to anticipate and adapt farming to maximize the agricultural production more effectively. Pearl millet being a climate-resilient crop is important to minimize the adverse effects of climate change and has the potential to increase income and food security of farming communities in arid regions. Pearl millet has a deep root system and can survive in a wide range of ecological conditions under water scarcity. It has high photosynthetic efficiency with an excellent productivity and growth in low nutrient soil conditions and is less reliant on chemical fertilizers. These attributes have made it a crop of choice for cultivation in arid and semi-arid regions of the world; however, fewer efforts have been made to study the climate-resilient features of pearl millet in comparison to the other major cereals. Several hybrids and varieties of pearl millet were developed during the past 50 years in India by both the public and private sectors. Pearl millet is also nutritionally superior and rich in micronutrients such as iron and zinc and can mitigate malnutrition and hidden hunger. Inclusion of minimum standards for micronutrients-grain iron and zinc content in the cultivar release policy-is the first of its kind step taken in pearl millet anywhere in the world, which can lead toward enhanced food and nutritional security. The availability of high-quality whole-genome sequencing and re-sequencing information of several lines may aid genomic dissection of stress tolerance and provide a good opportunity to further exploit the nutritional and climate-resilient attributes of pearl millet. Hence, more efforts should be put into its genetic enhancement and improvement in inheritance to exploit it in a better way. Thus, pearl millet is the next-generation crop holding the potential of nutritional richness and the climate resilience and efforts must be targeted to develop nutritionally dense hybrids/varieties tolerant to drought using different omics approaches.

NTRK fusions in colorectal cancer: clinical meaning and future perspective

INTRODUCTION

Despite the efforts of the scientific community, the prognosis of metastatic colorectal cancer (mCRC) remains poor. Actionable gene fusions such as Neurotrophic Tropomyosin Receptor Kinases (NTRK) rearrangements are rare but might represent a new target to improve outcomes in this setting. The first-generation TRK inhibitors, larotrectinib and entrectinib, have demonstrated efficacy and safety in mCRC cancer patients exhibiting NTRK pathogenic fusions. Moreover, second-generation molecules are emerging, able to overcome the acquired resistance to NTRK blocking.

AREAS COVERED

This review aims to report the current knowledge and the available evidence on NTRK fusion in mCRC, with a focus on molecular bases, clinical characteristics, prognostic meaning, and new therapeutic approaches, from the perspective of the clinical oncologist.

EXPERT OPINION

Considering the limited options associated with the treatment of mCRC patients, the possibility of identifying new molecular biomarkers is an urgent clinical need. The availability of new molecular targets and the combinations of different agents might represent the true breakthrough point, allowing for change in the clinical course of colorectal cancer patients.