Gene discovery and annotation using LCM-454 transcriptome sequencing

A comprehensive review of the applications of RNA sequencing in celiac disease research

RNA sequencing (RNA-seq) has undergone substantial advancements in recent decades and has emerged as a vital technique for profiling the transcriptome. The transition from bulk sequencing to single-cell and spatial approaches has facilitated the achievement of higher precision at cell resolution. It provides valuable biological knowledge about individual immune cells and aids in the discovery of the molecular mechanisms that contribute to the development of autoimmune diseases. Celiac disease (CeD) is an autoimmune disorder characterized by a strong immune response to gluten consumption. RNA-seq has led to significantly advanced research in multiple fields, particularly in CeD research. It has been instrumental in studies involving comparative transcriptomics, nutritional genomics and wheat research, cancer research in the context of CeD, genetic and noncoding RNA-mediated epigenetic insights, disease monitoring and biomarker discovery, regulation of mitochondrial functions, therapeutic target identification and drug mechanism of action, dietary factors, immune cell profiling and the immune landscape. This review offers a comprehensive examination of recent RNA-seq technology research in the field of CeD, highlighting future challenges and opportunities for its application.

Unraveling aging from transcriptomics

Research into aging constitutes a pivotal endeavor aimed at elucidating the underlying biological mechanisms governing aging and age-associated diseases, as well as promoting healthy longevity. Recent advances in transcriptomic technologies, such as bulk RNA sequencing (RNA-seq), single-cell transcriptomics, and spatial transcriptomics, have revolutionized our ability to study aging at unprecedented resolution and scale. These technologies present novel opportunities for the discovery of biomarkers, elucidation of molecular pathways, and development of targeted therapeutic strategies for age-related disorders. This review surveys recent breakthroughs in different types of transcripts on aging, such as mRNA, long noncoding (lnc)RNA, tRNA, and miRNA, highlighting key findings and discussing their potential implications for future studies in this field.

NERD-seq: a novel approach of Nanopore direct RNA sequencing that expands representation of non-coding RNAs

Non-coding RNAs (ncRNAs) are frequently documented RNA modification substrates. Nanopore Technologies enables the direct sequencing of RNAs and the detection of modified nucleobases. Ordinarily, direct RNA sequencing uses polyadenylation selection, studying primarily mRNA gene expression. Here, we present NERD-seq, which enables detection of multiple non-coding RNAs, excluded by the standard approach, alongside natively polyadenylated transcripts. Using neural tissues as a proof of principle, we show that NERD-seq expands representation of frequently modified non-coding RNAs, such as snoRNAs, snRNAs, scRNAs, srpRNAs, tRNAs, and rRFs. NERD-seq represents an RNA-seq approach to simultaneously study mRNA and ncRNA epitranscriptomes in brain tissues and beyond.

Landscape of Differentiation Potentials as a "Hallmark" in Oral-derived MSCs

Background

Mesenchymal stem cells (MSCs) offer clinical promise for use in cell therapy approaches for regenerative medicine. A therapeutic challenge is that MSCs from different tissues are phenotypically and functionally distinct. Therefore, this study aims to molecularly characterize oral-derived MSCs by defining one of the three hallmarks of MSCs, differentiation potential, to discern their true molecular identities.

Methods

Three different populations of oral tissue MSCs (from alveolar bone-aBMSCs; from dental pulp-DPSCs; and from gingiva-GMSCs) from three different patients were isolated and cultured. These MSCs were characterized for their stemness by flow cytometry and multi-differentiation potential, and their RNA was also isolated and analyzed quantitatively with RNA sequencing. Total mRNA-seq was performed and differentially expressed genes (DEGs) were identified in pairwise (DPSCs vs. aBMSCs, GMSCs vs. aBMSCs, and GMSCs vs. DPSCs) and tissue-specific comparisons (aBMSCs vs. Others, DPSCs vs. Others, GMSCs vs. Others) (FDR, p<0.05 ). Further, these DEGs, either common between MSC populations or unique to a specific MSC population, were evaluated for pathways and biological processes.

Results

aBMSCs, DPSCs, and GMSCs were successfully isolated and characterized. The tissue-specific comparison revealed that DEGs were most numerous in DPSCs (693 genes) as compared to aBMSCs (103 genes) or DPSCs (232 genes). Statistically significant DEGs through pairwise comparisons present higher numbers in GMSCs vs. DPSCs (627) as compared to either DPSCs vs aBMSCs (286) or GMSCs vs. aBMSCs (82). Further analysis found that RUNX2, IBSP, SOX6, ACAN, and VCAM1 were significantly upregulated in aBMSCs. In DPSCs, BMP4 and IL6 were significantly downregulated, whereas AXL and NES were significantly upregulated. In GMSCs, AGPT1, SEMA4D, and PGDFA were significantly downregulated. Additionally, MAPK, PI3-AKT, and RAS signaling pathways were significantly regulated in GMSCs. Interestingly, aBMSCs and DPSCs revealed positive regulation of osteoblast differentiation, whereas GMSCs revealed negative regulation of osteoblast differentiation. DPSCs also revealed negative regulation of angiogenesis.

Conclusions

Oral-derived MSCs have an inherent "landscape" of differentiation defined by their tissue of origin; yet this differentiation potential can be modulated by their microenvironment.

siqRNA-seq is a spike-in-independent technique for quantitative mapping of mRNA landscape

BACKGROUND

RNA sequencing (RNA-seq) is widely used for gene expression profiling and quantification. Quantitative RNA sequencing usually requires cell counting and spike-in, which is not always applicable to many samples. Here, we present a novel quantitative RNA sequencing method independent of spike-ins or cell counting, named siqRNA-seq, which can be used to quantitatively profile gene expression by utilizing gDNA as an internal control. Single-stranded library preparation used in siqRNA-seq profiles gDNA and cDNA with equal efficiency.

RESULTS

To quantify mRNA expression levels, siqRNA-seq constructs libraries for total nucleic acid to establish a model for expression quantification. Compared to Relative Quantification RNA-seq, siqRNA-seq is technically reliable and reproducible for expression profiling but also can sequence reads from gDNA which can be used as an internal reference for accurate expression quantification. Applying siqRNA-seq to investigate the effects of actinomycin D on gene expression in HEK293T cells, we show the advantages of siqRNA-seq in accurately identifying differentially expressed genes between samples with distinct global mRNA levels. Furthermore, we analyzed factors influencing the downward trend of gene expression regulated by ActD using siqRNA-seq and found that mRNA with m6A modification exhibited a faster decay rate compared to mRNA without m6A modification. Additionally, applying this technique to the quantitative analysis of seven tumor cell lines revealed a high degree of diversity in total mRNA expression among tumor cell lines.

CONCLUSIONS

Collectively, siqRNA-seq is a spike-in independent quantitative RNA sequencing method, which creatively uses gDNA as an internal reference to absolutely quantify gene expression. We consider that siqRNA-seq provides a convenient and versatile method to quantitatively profile the mRNA landscape in various samples.

Developing a simple and rapid method for cell-specific transcriptome analysis through laser microdissection: insights from citrus rind with broader implications

BACKGROUND

With the rapid development of single-cell sequencing technology, histological studies are no longer limited to conventional homogenized tissues. Laser microdissection enables the accurate isolation of specific tissues or cells, and when combined with next-generation sequencing, it can reveal important biological processes at the cellular level. However, traditional laser microdissection techniques have often been complicated and time-consuming, and the quality of the RNA extracted from the collected samples has been inconsistent, limiting follow-up studies. Therefore, an improved, simple, and efficient laser microdissection method is urgently needed.

RESULTS

We omitted the sample fixation and cryoprotectant addition steps. Instead, fresh samples were embedded in Optimal Cutting Temperature medium within 1.5 ml centrifuge tube caps, rapidly frozen with liquid nitrogen, and immediately subjected to cryosectioning. A series of section thicknesses of citrus rind were tested for RNA extraction, which showed that 18 μm thickness yielded the highest quality RNA. By shortening the dehydration time to one minute per ethanol gradient and omitting the tissue clearing step, the resulting efficient dehydration and preserved morphology ensured high-quality RNA extraction. We also propose a set of laser microdissection parameters by adjusting the laser power to optimal values, reducing the aperture size, and lowering the pulse frequency. Both the epidermal and subepidermal cells from the citrus rind were collected, and RNA extraction was completed within nine hours. Using this efficient method, the transcriptome sequencing of the isolated tissues generated high-quality data with average Q30 values and mapping rates exceeding 91%. Moreover, the transcriptome analysis revealed significant differences between the cell layers, further confirming the effectiveness of our isolation approach.

CONCLUSIONS

We developed a simple and rapid laser microdissection method and demonstrated its effectiveness through a study based on citrus rind, from which we generated high-quality transcriptomic data. This fast and efficient method of cell isolation, combined with transcriptome sequencing not only contributes to precise histological studies at the cellular level in citrus but also provides a promising approach for cell-specific transcriptome analysis in a broader range of other plant tissues.

Application of single-cell sequencing to the research of tumor microenvironment

Single-cell sequencing is a technique for detecting and analyzing genomes, transcriptomes, and epigenomes at the single-cell level, which can detect cellular heterogeneity lost in conventional sequencing hybrid samples, and it has revolutionized our understanding of the genetic heterogeneity and complexity of tumor progression. Moreover, the tumor microenvironment (TME) plays a crucial role in the formation, development and response to treatment of tumors. The application of single-cell sequencing has ushered in a new age for the TME analysis, revealing not only the blueprint of the pan-cancer immune microenvironment, but also the heterogeneity and differentiation routes of immune cells, as well as predicting tumor prognosis. Thus, the combination of single-cell sequencing and the TME analysis provides a unique opportunity to unravel the molecular mechanisms underlying tumor development and progression. In this review, we summarize the recent advances in single-cell sequencing and the TME analysis, highlighting their potential applications in cancer research and clinical translation.

Transcriptome profiling analysis of uterus during chicken laying periods

The avian eggshell is formed in the uterus. Changes in uterine function may have a significant effect on eggshell quality. To identify the vital genes impacting uterine functional maintenance in the chicken, uteri in three different periods (22W, 31W, 51W) were selected for RNA sequencing and bioinformatics analysis. In our study, 520, 706 and 736 differentially expressed genes (DEGs) were respectively detected in the W31 vs W22 group, W51 vs W31 group and W51 vs W22 group. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis indicated DEGs were enriched in the extracellular matrix, extracellular region part, extracellular region, extracellular matrix structural constituent, ECM receptor interaction, collagen-containing extracellular matrix and collagen trimer in the uterus (P < 0.05). Protein-protein interaction analysis revealed that FN1, LOX, THBS2, COL1A1, COL1A2, COL5A1, COL5A2, POSTN, MMP13, VANGL2, RAD54B, SPP1, SDC1, BTC, ANGPTL3 might be key candidate genes for uterine functional maintenance in chicken. This study discovered dominant genes and pathways which enhanced our knowledge of chicken uterine functional maintenance.

The Lost and Found: Unraveling the Functions of Orphan Genes

Orphan Genes (OGs) are a mysterious class of genes that have recently gained significant attention. Despite lacking a clear evolutionary history, they are found in nearly all living organisms, from bacteria to humans, and they play important roles in diverse biological processes. The discovery of OGs was first made through comparative genomics followed by the identification of unique genes across different species. OGs tend to be more prevalent in species with larger genomes, such as plants and animals, and their evolutionary origins remain unclear but potentially arise from gene duplication, horizontal gene transfer (HGT), or de novo origination. Although their precise function is not well understood, OGs have been implicated in crucial biological processes such as development, metabolism, and stress responses. To better understand their significance, researchers are using a variety of approaches, including transcriptomics, functional genomics, and molecular biology. This review offers a comprehensive overview of the current knowledge of OGs in all domains of life, highlighting the possible role of dark transcriptomics in their evolution. More research is needed to fully comprehend the role of OGs in biology and their impact on various biological processes.

SPECK: an unsupervised learning approach for cell surface receptor abundance estimation for single-cell RNA-sequencing data

Summary

The rapid development of single-cell transcriptomics has revolutionized the study of complex tissues. Single-cell RNA-sequencing (scRNA-seq) can profile tens-of-thousands of dissociated cells from a tissue sample, enabling researchers to identify cell types, phenotypes and interactions that control tissue structure and function. A key requirement of these applications is the accurate estimation of cell surface protein abundance. Although technologies to directly quantify surface proteins are available, these data are uncommon and limited to proteins with available antibodies. While supervised methods that are trained on Cellular Indexing of Transcriptomes and Epitopes by Sequencing data can provide the best performance, these training data are limited by available antibodies and may not exist for the tissue under investigation. In the absence of protein measurements, researchers must estimate receptor abundance from scRNA-seq data. Therefore, we developed a new unsupervised method for receptor abundance estimation using scRNA-seq data called SPECK (Surface Protein abundance Estimation using CKmeans-based clustered thresholding) and primarily evaluated its performance against unsupervised approaches for at least 25 human receptors and multiple tissue types. This analysis reveals that techniques based on a thresholded reduced rank reconstruction of scRNA-seq data are effective for receptor abundance estimation, with SPECK providing the best overall performance.

Availability and implementation

SPECK is freely available at https://CRAN.R-project.org/package=SPECK.

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

RNA-Seq analysis of Phanerochaete sordida YK-624 degrades neonicotinoid pesticide acetamiprid

Acetamiprid (ACE) belongs to the group of neonicotinoid pesticides, which have become the most widely utilised pesticides around the world in the last two decades. The ability of Phanerochaete sordida YK-624 to degrade ACE under ligninolytic conditions has been demonstrated; however, the functional genes involved in ACE degradation have not been fully elucidated. In the present study, the differentially expressed genes of P. sordida YK-624 under ACE-degrading conditions and in the absence of ACE were elucidated by RNA sequencing (RNA-Seq). Based on the gene ontology enrichment results, the cell wall and cell membrane were significantly affected under ACE-degrading conditions. This result suggested that intracellular degradation of ACE might be mediated by this fungus. In addition, genes in metabolic pathways were the most enriched upregulated differentially expressed genes according to the KEGG pathway analysis. Eleven differentially expressed genes characterised as cytochrome P450s were upregulated, and these genes were determined to be particularly important for ACE degradation by P. sordida YK-624 under ligninolytic conditions.

Fibrosis in Pathology of Heart and Kidney: From Deep RNA-Sequencing to Novel Molecular Targets

Diseases of the heart and the kidney, including heart failure and chronic kidney disease, can dramatically impair life expectancy and the quality of life of patients. The heart and kidney form a functional axis; therefore, functional impairment of 1 organ will inevitably affect the function of the other. Fibrosis represents the common final pathway of diseases of both organs, regardless of the disease entity. Thus, inhibition of fibrosis represents a promising therapeutic approach to treat diseases of both organs and to resolve functional impairment. However, despite the growing knowledge in this field, the exact pathomechanisms that drive fibrosis remain elusive. RNA-sequencing approaches, particularly single-cell RNA-sequencing, have revolutionized the investigation of pathomechanisms at a molecular level and facilitated the discovery of disease-associated cell types and mechanisms. In this review, we give a brief overview over the evolution of RNA-sequencing techniques, summarize most recent insights into the pathogenesis of heart and kidney fibrosis, and discuss how transcriptomic data can be used, to identify new drug targets and to develop novel therapeutic strategies.

An Angiogenic Gene Signature for Prediction of the Prognosis and Therapeutic Responses of Hepatocellular Carcinoma

Among cancer-related deaths worldwide, hepatocellular carcinoma (HCC) ranks second. The hypervascular feature of most HCC underlines the importance of angiogenesis in therapy. This study aimed to identify the key genes which could characterize the angiogenic molecular features of HCC and further explore therapeutic targets to improve patients' prognosis. Public RNAseq and clinical data are from TCGA, ICGC, and GEO. Angiogenesis-associated genes were downloaded from the GeneCards database. Then, we used multi-regression analysis to generate a risk score model. This model was trained on the TCGA cohort (n = 343) and validated on the GEO cohort (n = 242). The predicting therapy in the model was further evaluated by the DEPMAP database. We developed a fourteen-angiogenesis-related gene signature that was distinctly associated with overall survival (OS). Through the nomograms, our signature was proven to possess a better predictive role in HCC prognosis. The patients in higher-risk groups displayed a higher tumor mutation burden (TMB). Interestingly, our model could group subsets of patients with different sensitivities to immune checkpoint inhibitors (ICIs) and Sorafenib. We also predicted that Crizotinib, an anti-angiogenic drug, might be more sensitive to these patients with high-risk scores by the DEPMAP. The inhibitory effect of Crizotinib in human vascular cells was obvious in vitro and in vivo. This work established a novel HCC classification based on the gene expression values of angiogenesis genes. Moreover, we predicted that Crizotinib might be more effective in the high-risk patients in our model.

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.

Single-cell RNA sequencing in the context of neuropathic pain: progress, challenges, and prospects

Neuropathic pain, characterized by persistent or intermittent spontaneous pain as well as some unpleasant abnormal sensations, is one of the most prevalent health problems in the world. Ectopic nerve activity, central and peripheral nociceptive sensitization and many other potential mechanisms may participate in neuropathic pain. The complexity and ambiguity of neuropathic pain mechanisms result in difficulties in pain management, and existing treatment plans provide less-than-satisfactory relief. In recent years, single-cell RNA sequencing (scRNA-seq) has been increasingly applied and has become a powerful means for biological researchers to explore the complexity of neurobiology. This technique can be used to perform unbiased, high-throughput and high-resolution transcriptional analyses of neuropathic pain-associated cells, improving the understanding of neuropathic pain mechanisms and enabling individualized pain management. To date, scRNA-seq has been preliminarily used in neuropathic pain research for applications such as compiling a dorsal root ganglion atlas, identifying new cell types and discovering gene regulatory networks associated with neuropathic pain. Although scRNA-seq is a relatively new technique in the neuropathic pain field, there have been several studies based on animal models. However, because of the various differences between animals and humans, more attention should be given to translational medicine research. With the aid of scRNA-seq, researchers can further explore the mechanism of neuropathic pain to improve the clinical understanding of the diagnosis, treatment and management of neuropathic pain.

GeneFriends: gene co-expression databases and tools for humans and model organisms

Gene co-expression analysis has emerged as a powerful method to provide insights into gene function and regulation. The rapid growth of publicly available RNA-sequencing (RNA-seq) data has created opportunities for researchers to employ this abundant data to help decipher the complexity and biology of genomes. Co-expression networks have proven effective for inferring the relationship between the genes, for gene prioritization and for assigning function to poorly annotated genes based on their co-expressed partners. To facilitate such analyses we created previously an online co-expression tool for humans and mice entitled GeneFriends. To continue providing a valuable tool to the scientific community, we have now updated the GeneFriends database and website. Here, we present the new version of GeneFriends, which includes gene and transcript co-expression networks based on RNA-seq data from 46 475 human and 34 322 mouse samples. The new database also encompasses tissue-specific gene co-expression networks for 20 human and 21 mouse tissues, dataset-specific gene co-expression maps based on TCGA and GTEx projects and gene co-expression networks for additional seven model organisms (fruit fly, zebrafish, worm, rat, yeast, cow and chicken). GeneFriends is freely available at http://www.genefriends.org/.

Sequential Isolation of Microglia and Astrocytes from Young and Aged Adult Mouse Brains for Downstream Transcriptomic Analysis

In aging, the brain is more vulnerable to injury and neurodegenerative disease, but the mechanisms responsible are largely unknown. Evidence now suggests that neuroinflammation, mediated by resident brain astrocyte and microglia populations, are key players in the generation of inflammatory responses and may influence both age related processes and the initiation/progression of neurodegeneration. Consequently, targeting these cell types individually and collectively may aid in the development of novel disease-modifying therapies. We have optimized and characterized a protocol for the effective sequential isolation of both microglia and astrocytes from the adult mouse brain in young and aged mice. We demonstrate a technique for the sequential isolation of these immune cells by using magnetic beads technology, optimized to increase yield and limit potential artifacts in downstream transcriptomic applications, including RNA-sequencing pipelines. This technique is versatile, cost-effective, and reliable for the study of responses within the same biological context, simultaneously being advantageous in reducing mice numbers required to assess cellular responses in normal and age-related pathological conditions.

Promoting validation and cross-phylogenetic integration in model organism research

Model organism (MO) research provides a basic understanding of biology and disease due to the evolutionary conservation of the molecular and cellular language of life. MOs have been used to identify and understand the function of orthologous genes, proteins, cells and tissues involved in biological processes, to develop and evaluate techniques and methods, and to perform whole-organism-based chemical screens to test drug efficacy and toxicity. However, a growing richness of datasets and the rising power of computation raise an important question: How do we maximize the value of MOs? In-depth discussions in over 50 virtual presentations organized by the National Institutes of Health across more than 10 weeks yielded important suggestions for improving the rigor, validation, reproducibility and translatability of MO research. The effort clarified challenges and opportunities for developing and integrating tools and resources. Maintenance of critical existing infrastructure and the implementation of suggested improvements will play important roles in maintaining productivity and facilitating the validation of animal models of human biology and disease.

Bulk RNA-Seq Analysis Reveals Differentially Expressed Genes Associated with Lateral Branch Angle in Peanut

Lateral branch angle (LBA), or branch habit, is one of the most important agronomic traits in peanut. To date, the underlying molecular mechanisms of LBA have not been elucidated in peanut. To acquire the differentially expressed genes (DEGs) related to LBA, a TI population was constructed through the hybridization of a bunch-type peanut variety Tifrunner and prostrate-type Ipadur. We report the identification of DEGs related to LBA by sequencing two RNA pools, which were composed of 45 F₃ lines showing an extreme opposite bunch and prostrate phenotype. We propose to name this approach Bulk RNA-sequencing (BR-seq) as applied to several plant species. Through BR-seq analysis, a total of 3083 differentially expressed genes (DEGs) were identified, including 13 gravitropism-related DEGs, 22 plant hormone-related DEGs, and 55 transcription factors-encoding DEGs. Furthermore, we also identified commonly expressed alternatively spliced (AS) transcripts, of which skipped exon (SE) and retained intron (RI) were most abundant in the prostrate and bunch-type peanut. AS isoforms between prostrate and bunch peanut highlighted important clues to further understand the post-transcriptional regulatory mechanisms of branch angle regulation. Our findings provide not only important insights into the landscape of the regulatory pathway involved in branch angle formation but also present practical information for peanut molecular breeding in the future.

Transcriptome analysis provides new insights into cold adaptation of corsac fox ( Vulpes Corsac )

Vulpesare widely distributed throughout the world and have undergone drastic physiological and phenotypic changes in response to their environment. However, little is known about the underlying genetic causes of these traits, especially Vulpes corsac. In this study, RNA‐Seq was used to obtain a comprehensive dataset for multiple pooled tissues of corsac fox, and selection analysis of orthologous genes was performed to identify the genes that may be influenced by the low‐temperature environment. More than 6.32 Gb clean reads were obtained and assembled into a total of 173,353 unigenes with an average length of 557 bp for corsac fox. Selective pressure analysis showed that 16 positively selected genes (PSGs) were identified in corsac fox, red fox, and arctic fox. Enrichment analysis of PSGs showed that the LRP11 gene was enriched in several pathways related to the low‐temperature response and might play a key role in response to environmental stimuli of foxes. In addition, several positively selected genes were related to DNA damage repair (ELP2 and CHAF1A), innate immunity (ARRDC4 and S100A12), and the respiratory chain (NDUFA5), and these positively selected genes might play a role in adaptation to harsh wild fox environments. The results of common orthologous gene analysis showed that gene flow or convergent evolution might be an important factor in promoting regional differentiation of foxes. Our study provides a valuable transcriptomic resource for the evolutionary history of the corsac fox and the adaptations to the extreme environments.

RNA sequencing and its applications in cancer and rare diseases

With the invention of RNA sequencing over a decade ago, diagnosis and identification of the gene-related diseases entered a new phase that enabled more accurate analysis of the diseases that are difficult to approach and analyze. RNA sequencing has availed in-depth study of transcriptomes in different species and provided better understanding of rare diseases and taxonomical classifications of various eukaryotic organisms. Development of single-cell, short-read, long-read and direct RNA sequencing using both blood and biopsy specimens of the organism together with recent advancement in computational analysis programs has made the medical professional's ability in identifying the origin and cause of genetic disorders indispensable. Altogether, such advantages have evolved the treatment design since RNA sequencing can detect the resistant genes against the existing therapies and help medical professions to take a further step in improving methods of treatments towards higher effectiveness and less side effects. Therefore, it is of essence to all researchers and scientists to have deeper insight in all available methods of RNA sequencing while taking a step-in therapy design.

Selection and validation of reference genes for measuring gene expression in Piper species at different life stages using RT-qPCR analysis

The secondary metabolism of Piper species is known to produce a myriad of natural products from various biosynthetic pathways which, represent a rich source of previously uncharacterized chemical compounds. The determination of gene expression profiles in multiple tissue/organ samples could provide valuable clues towards understanding the potential biological functions of chemical changes in these plants. Studies on gene expression by RT-qPCR require particularly careful selection of suitable reference genes as a control for normalization. Here, we provide a study for the identification of reliable reference genes in P. arboreum, P. gaudichaudianum, P. malacophyllum, and P. tuberculatum, at two different life stages: 2-month-old seedlings and adult plants. To do this, annotated sequences were recovered from transcriptome datasets of the above listed Piper spp. These sequences were subjected to expression analysis using RT-qPCR, followed by analysis using the geNorm and NormFinder algorithms. A set of five genes were identified showing stable expression: ACT7 (Actin-7), Cyclophilin (Peptidyl-prolyl cis-trans isomerase), EF1α (Elongation factor 1-alpha), RNABP (RNA-binding protein), and UBCE (Ubiquitin conjugating enzyme). The universality of these genes was then validated using two target genes, ADC (arginine decarboxylase) and SAMDC (S-adenosylmethionine decarboxylase), which are involved in the biosynthesis of polyamines. We showed that normalization genes varied according to Piper spp., and we provide a list of recommended pairs of the best combination for each species. This study provides the first set of suitable candidate genes for gene expression studies in the four Piper spp. assayed, and the findings will facilitate subsequent transcriptomic and functional gene research.

Inhibitory Effect and Potential Mechanism of Lactobacillus plantarum YE4 against Dipeptidyl Peptidase-4

This study investigated the inhibitory effect and mechanism of 12 LAB strains isolated from Chinese fermented foods on dipeptidyl peptidase-4 (DPP-4) using the Caco-2 cell model. The results showed that the inhibitory effect of cell-free extracts (CFEs) collected from each LAB strain on DPP-4 was higher than that of the cell-free excretory supernatants. The CFEs from Lactobacillus plantarum YE4 (YE4-CFE) exhibited the strongest DPP-4 inhibitory activity (24.33% inhibition). Furthermore, YE4-CFE altered the TNF and MAPK signaling pathways. Additionally, the YE4-CFE ultrafiltration fraction (<3 kDa) displayed a similar DPP-4 inhibitory activity to YE4-CFE. UHPLC-MS/MS identified 19 compounds with a relative proportion of more than 1% in the <3 kDa fraction, and adenine, acetylcholine, and L-phenylalanine were the top three substances in terms of proportion. Altogether, the inhibitory effect of YE4-CFE on DPP-4 was associated with the TNF and MAPK signaling pathways, and with the high proportion of adenine, acetylcholine, and L-phenylalanine.

De novo assembly, transcriptome characterization and marker discovery in Indian major carp, Labeo rohita through pyrosequencing

Labeo rohita, one of the Indian major carps, is the most popular culture species in Indian subcontinent due to its consumer preference and delicacy. A selective breeding program for harvest body weight has resulted in an average genetic gain of 17% per generation. Transcriptome resource for this species is scanty. Here, we have characterized the liver and muscle transcriptomes of rohu using Roche 454 GS-FLX next generation sequencing platform. In total, 1.2 million reads were generated, de novo assembly and clustering resulted in 4171 transcripts. Out of these, 4171 had significant blast hit against NCBI nr database, and 2130 transcripts were successfully annotated. In total, 289 SSRs were identified with an identification rate of 5.8%, and dinucleotide repeat motifs were observed to be the most abundant SSRs. Further, 2231 putative SNPs were identified with high confidence. Validation of eight putative SNPs using Sanger sequencing resulted in 100% true SNPs. Significant allelic imbalance of M1, M4 and M5 loci between growth selected and control individual were observed. Furthermore, 13 transcription factors were identified in the present study belonging to six different transcription factor families. The present study demonstrated the utility of RNAseq to develop genomics resources in non-model fish species, and the marker resources developed would support the genetic improvement program of this species.

Comprehensive Analysis of Large-Scale Transcriptomes from Multiple Cancer Types

Various abnormalities of transcriptional regulation revealed by RNA sequencing (RNA-seq) have been reported in cancers. However, strategies to integrate multi-modal information from RNA-seq, which would help uncover more disease mechanisms, are still limited. Here, we present PipeOne, a cross-platform one-stop analysis workflow for large-scale transcriptome data. It was developed based on Nextflow, a reproducible workflow management system. PipeOne is composed of three modules, data processing and feature matrices construction, disease feature prioritization, and disease subtyping. It first integrates eight different tools to extract different information from RNA-seq data, and then used random forest algorithm to study and stratify patients according to evidences from multiple-modal information. Its application in five cancers (colon, liver, kidney, stomach, or thyroid; total samples n = 2024) identified various dysregulated key features (such as PVT1 expression and ABI3BP alternative splicing) and pathways (especially liver and kidney dysfunction) shared by multiple cancers. Furthermore, we demonstrated clinically-relevant patient subtypes in four of five cancers, with most subtypes characterized by distinct driver somatic mutations, such as TP53, TTN, BRAF, HRAS, MET, KMT2D, and KMT2C mutations. Importantly, these subtyping results were frequently contributed by dysregulated biological processes, such as ribosome biogenesis, RNA binding, and mitochondria functions. PipeOne is efficient and accurate in studying different cancer types to reveal the specificity and cross-cancer contributing factors of each cancer.It could be easily applied to other diseases and is available at GitHub.

From bulk, single-cell to spatial RNA sequencing

RNA sequencing (RNAseq) can reveal gene fusions, splicing variants, mutations/indels in addition to differential gene expression, thus providing a more complete genetic picture than DNA sequencing. This most widely used technology in genomics tool box has evolved from classic bulk RNA sequencing (RNAseq), popular single cell RNA sequencing (scRNAseq) to newly emerged spatial RNA sequencing (spRNAseq). Bulk RNAseq studies average global gene expression, scRNAseq investigates single cell RNA biology up to 20,000 individual cells simultaneously, while spRNAseq has ability to dissect RNA activities spatially, representing next generation of RNA sequencing. This article highlights these technologies, characteristic features and suitable applications in precision oncology.

Protocol for RNA-seq Expression Analysis in Yeast

Genome-wide sequencing of RNA (RNA-seq) has become an inexpensive tool to gain key insights into cellular and disease mechanisms. Sample preparation and sequencing are streamlined and allow the acquisition of hundreds of gene expression profiles in a few days; however, in particular, data processing, curation, and analysis involve numerous steps that can be overwhelming to non-experts. Here, the sample preparation, sequencing, and data processing workflow for RNA-seq expression analysis in yeast is described. While this protocol covers only a small portion of the RNA-seq landscape, the principal workflow common to such experiments is described, allowing the reader to adapt the protocol where necessary. Graphic abstract: Basic workflow of RNA-seq expression analysis.

Deploying new generation sequencing for the study of flesh color depletion in Atlantic Salmon (Salmo salar)

BACKGROUND

The flesh pigmentation of farmed Atlantic salmon is formed by accumulation of carotenoids derived from commercial diets. In the salmon gastrointestinal system, the hindgut is considered critical in the processes of carotenoids uptake and metabolism. In Tasmania, flesh color depletion can noticeably affect farmed Atlantic salmon at different levels of severity following extremely hot summers. In this study, RNA sequencing (RNA-Seq) was performed to investigate the reduction in flesh pigmentation. Library preparation is a key step that significantly impacts the effectiveness of RNA sequencing (RNA-Seq) experiments. Besides the commonly used whole transcript RNA-Seq method, the 3' mRNA-Seq method is being applied widely, owing to its reduced cost, enabling more repeats to be sequenced at the expense of lower resolution. Therefore, the output of the Illumina TruSeq kit (whole transcript RNA-Seq) and the Lexogen QuantSeq kit (3' mRNA-Seq) was analyzed to identify genes in the Atlantic salmon hindgut that are differentially expressed (DEGs) between two flesh color phenotypes.

RESULTS

In both methods, DEGs between the two color phenotypes were associated with metal ion transport, oxidation-reduction processes, and immune responses. We also found DEGs related to lipid metabolism in the QuantSeq method. In the TruSeq method, a missense mutation was detected in DEGs in different flesh color traits. The number of DEGs found in the TruSeq libraries was much higher than the QuantSeq; however, the trend of DEGs in both library methods was similar and validated by qPCR.

CONCLUSIONS

Flesh coloration in Atlantic salmon is related to lipid metabolism in which apolipoproteins, serum albumin and fatty acid-binding protein genes are hypothesized to be linked to the absorption, transport and deposition of carotenoids. Our findings suggest that Grp could inhibit the feeding behavior of low color-banded fish, resulting in the dietary carotenoid shortage. Several SNPs in genes involving in carotenoid-binding cholesterol and oxidative stress were detected in both flesh color phenotypes. Regarding the choice of the library preparation method, the selection criteria depend on the research design and purpose. The 3' mRNA-Seq method is ideal for targeted identification of highly expressed genes, while the whole RNA-Seq method is recommended for identification of unknown genes, enabling the identification of splice variants and trait-associated SNPs, as we have found for duox2 and duoxa1.

Comparative transcriptome analysis reveals changes in gene expression in sea cucumber (Holothuria leucospilota) in response to acute temperature stress

Ambient temperature is an important abiotic factor that influences growth performance and physiological functions in sea cucumbers. To understand the molecular responses of the sea cucumber Holothuria leucospilota to acute temperature stress, we performed a de novo transcriptome analysis of body wall tissue from H. leucospilota exposed to 2 hoursh of acute heat (35 ± 1 °C) and cold stress (15 ± 1 °C). A total of 99,015 unigenes were obtained after assembly of the sequenced reads. Compared with a control group maintained at 25.0 ± 1 °C, 1169 differentially expressed unigenes (DEGs) were identified after heat stress, 781 were up-regulated and 388 were down-regulated. After cold stress, 1464 DEGs were identified; 900 were up-regulated and 564 were down-regulated. The annotation of DEGs revealed that heat shock proteins play important roles in protecting H. leucospilota from high temperature stress. Furthermore, KEGG pathway enrichment analysis showed that the categories: "Ribosome" and "Protein processing in endoplasmic reticulum" were strongly affected by heat stress. These two pathways are associated with biosynthesis and processing of proteins, and refolding of misfolded proteins. The lipid metabolism pathways "Sphingolipid metabolism" and "Ether lipid metabolism", were affected by cold stress. The RNA-Seq results for eight selected DEGs were verified the expression by quantitative real-time PCR analysis. Our results will improve the understanding of the molecular response mechanisms of H. leucospilota to ambient temperature stress.

Simultaneous profiling of Arabidopsis thaliana and Vibrio vulnificus MO6-24/O transcriptomes by dual RNA-seq analysis

We previously demonstrated that a marine bacterial pathogen Vibrio vulnificus isolated from sea foods modulated gene expression levels and defense responses of a land plant Arabidopsis thaliana. Although the interaction between V. vulnificus and A. thaliana was verified under artificial and greenhouse conditions, the simultaneous changes in host and pathogen transcriptomes remained obscure. In this study, we simultaneously analyzed the transcriptome of V. vulnificus MO6-24/O and A. thaliana by dual RNA-sequencing analysis. Disease symptoms appeared at 5 and 7 days post-inoculation in vitro and post-infiltration in planta, respectively. A total of 31, 128, 303, 219, and 130 differentially expressed genes (DEGs) were identified in V. vulnificus MO6-24/O at 3, 6, 12, 24, and 48 h post-infiltration. Out of these, 14 genes involved in the virulence and pathogenicity of V. vulnificus MO6 were characterized. These genes were clustered into six categories, including adherence, antiphagocytosis, chemotaxis and motility, iron uptake, toxin and secretion system. In plant side, the bacterium DEGs potentially played a pivotal role in activating pattern recognition receptors (PRRs)-mediated defense responses. A. thaliana genes related to PRRs, reactive oxygen species burst, mitogen-activated protein kinase cascade induction, salicylic acid, jasmonic acid, ethylene, abscisic acid, auxin, gibberellin, and cytokinin were highly induced by V. vulnificus MO6-24/O challenge. Taken together, our results indicate that the sophisticated communication between a marine bacterial pathogen V. vulnificus and A. thaliana occurs. It is the first report demonstration that V. vulnificus actively modulates its virulence factors and potential host immune regulator in a land plant species.

The epigenetic basis of cellular heterogeneity

Single-cell sequencing-based methods for profiling gene transcript levels have revealed substantial heterogeneity in expression levels among morphologically indistinguishable cells. This variability has important functional implications for tissue biology and disease states such as cancer. Mapping of epigenomic information such as chromatin accessibility, nucleosome positioning, histone tail modifications and enhancer-promoter interactions in both bulk-cell and single-cell samples has shown that these characteristics of chromatin state contribute to expression or repression of associated genes. Advances in single-cell epigenomic profiling methods are enabling high-resolution mapping of chromatin states in individual cells. Recent studies using these techniques provide evidence that variations in different aspects of chromatin organization collectively define gene expression heterogeneity among otherwise highly similar cells.

Applying genomic and transcriptomic advances to mitochondrial medicine

Next-generation sequencing (NGS) has increased our understanding of the molecular basis of many primary mitochondrial diseases (PMDs). Despite this progress, many patients with suspected PMD remain without a genetic diagnosis, which restricts their access to in-depth genetic counselling, reproductive options and clinical trials, in addition to hampering efforts to understand the underlying disease mechanisms. Although they represent a considerable improvement over their predecessors, current methods for sequencing the mitochondrial and nuclear genomes have important limitations, and molecular diagnostic techniques are often manual and time consuming. However, recent advances in genomics and transcriptomics offer realistic solutions to these challenges. In this Review, we discuss the current genetic testing approach for PMDs and the opportunities that exist for increased use of whole-genome NGS of nuclear and mitochondrial DNA (mtDNA) in the clinical environment. We consider the possible role for long-read approaches in sequencing of mtDNA and in the identification of novel nuclear genomic causes of PMDs. We examine the expanding applications of RNA sequencing, including the detection of cryptic variants that affect splicing and gene expression and the interpretation of rare and novel mitochondrial transfer RNA variants.

Non-Coding RNAs in Cancer Diagnosis and Therapy: Focus on Lung Cancer

Over the last several decades, clinical evaluation and treatment of lung cancers have largely improved with the classification of genetic drivers of the disease, such as EGFR, ALK, and ROS1. There are numerous regulatory factors that exert cellular control over key oncogenic pathways involved in lung cancers. In particular, non-coding RNAs (ncRNAs) have a diversity of regulatory roles in lung cancers such that they have been shown to be involved in inducing proliferation, suppressing apoptotic pathways, increasing metastatic potential of cancer cells, and acquiring drug resistance. The dysregulation of various ncRNAs in human cancers has prompted preclinical studies examining the therapeutic potential of restoring and/or inhibiting these ncRNAs. Furthermore, ncRNAs demonstrate tissue-specific expression in addition to high stability within biological fluids. This makes them excellent candidates as cancer biomarkers. This review aims to discuss the relevance of ncRNAs in cancer pathology, diagnosis, and therapy, with a focus on lung cancer.

Transcriptome and Comparative Chloroplast Genome Analysis of Vincetoxicum versicolor: Insights Into Molecular Evolution and Phylogenetic Implication

Vincetoxicum versicolor (Bunge) Decne is the original plant species of the Chinese herbal medicine Cynanchi Atrati Radix et Rhizoma. The lack of information on the transcriptome and chloroplast genome of V. versicolor hinders its evolutionary and taxonomic studies. Here, the V. versicolor transcriptome and chloroplast genome were assembled and functionally annotated. In addition, the comparative chloroplast genome analysis was conducted between the genera Vincetoxicum and Cynanchum. A total of 49,801 transcripts were generated, and 20,943 unigenes were obtained from V. versicolor. One thousand thirty-two unigenes from V. versicolor were classified into 73 functional transcription factor families. The transcription factors bHLH and AP2/ERF were the most significantly abundant, indicating that they should be analyzed carefully in the V. versicolor ecological adaptation studies. The chloroplast genomes of Vincetoxicum and Cynanchum exhibited a typical quadripartite structure with highly conserved gene order and gene content. They shared an analogous codon bias pattern in which the codons of protein-coding genes had a preference for A/U endings. The natural selection pressure predominantly influenced the chloroplast genes. A total of 35 RNA editing sites were detected in the V. versicolor chloroplast genome by RNA sequencing (RNA-Seq) data, and one of them restored the start codon in the chloroplast ndhD of V. versicolor. Phylogenetic trees constructed with protein-coding genes supported the view that Vincetoxicum and Cynanchum were two distinct genera.

RAP: A Web Tool for RNA-Seq Data Analysis

Since 1950 main studies of RNA regarded its role in the protein synthesis. Later insights showed that only a small portion of RNA codes for proteins where the rest could have different functional roles. With the advent of Next Generation Sequencing (NGS) and in particular with RNA-seq technology the cost of sequencing production dropped down. Among the NGS application areas, the transcriptome analysis, that is, the analysis of transcripts in a cell, their quantification for a specific developmental stage or treatment condition, became more and more adopted in the laboratories. As a consequence in the last decade new insights were gained in the understanding of both transcriptome complexity and involvement of RNA molecules in cellular processes. For what concerns computational advances, bioinformatics research developed new methods for analyzing RNA-seq data. The comparison among transcriptome profiles from several samples is often a difficult task for nonexpert programmers. Here, in this chapter, we introduce RAP (RNA-Seq Analysis Pipeline), a completely automated web tool for transcriptome analysis. It is a user-friendly web tool implementing a detailed transcriptome workflow to detect differential expressed genes and transcript, identify spliced junctions and constitutive or alternative polyadenylation sites and predict gene fusion events. Through the web interface the researchers can get all this information without any knowledge of the underlying High Performance Computing infrastructure.

Coupled Transcriptomics for Differential Expression Analysis and Determination of Transcription Start Sites: Design and Bioinformatics

The term coupled transcriptomics is coined to describe a design of an RNA-seq experiment intended for both differential expression analysis and genome-wide determination of the transcription start sites (TSS). The minimal requirements for the first analysis are two experimental conditions with at least two biological replicates enabling statistical tests. The second analysis involves the bioinformatics comparison of the data generated from a control RNA-seq library with another library enriched in primary transcripts using Terminator^™ 5'-phosphate-dependent exonuclease, in an experiment denominated differential RNA-seq (dRNA-seq). Usually, dRNA-seq is carried out with specific protocols for library construction, different of those used for common differential expression analysis. Our experimental design allows to use the same data for both analyses, reducing the number of libraries to be generated and sequenced. This is a guide for designing a coupled transcriptomics experiment and for the subsequent bioinformatics procedures. The proposed methods can be applied to the detection and study of small RNA genes.

Exploring chromatin conformation and gene co-expression through graph embedding

MOTIVATION

The relationship between gene co-expression and chromatin conformation is of great biological interest. Thanks to high-throughput chromosome conformation capture technologies (Hi-C), researchers are gaining insights on the tri-dimensional organization of the genome. Given the high complexity of Hi-C data and the difficult definition of gene co-expression networks, the development of proper computational tools to investigate such relationship is rapidly gaining the interest of researchers. One of the most fascinating questions in this context is how chromatin topology correlates with gene co-expression and which physical interaction patterns are most predictive of co-expression relationships.

RESULTS

To address these questions, we developed a computational framework for the prediction of co-expression networks from chromatin conformation data. We first define a gene chromatin interaction network where each gene is associated to its physical interaction profile; then, we apply two graph embedding techniques to extract a low-dimensional vector representation of each gene from the interaction network; finally, we train a classifier on gene embedding pairs to predict if they are co-expressed. Both graph embedding techniques outperform previous methods based on manually designed topological features, highlighting the need for more advanced strategies to encode chromatin information. We also establish that the most recent technique, based on random walks, is superior. Overall, our results demonstrate that chromatin conformation and gene regulation share a non-linear relationship and that gene topological embeddings encode relevant information, which could be used also for downstream analysis.

AVAILABILITY AND IMPLEMENTATION

The source code for the analysis is available at: https://github.com/marcovarrone/gene-expression-chromatin.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Profiling Novel Alternative Splicing within Multiple Tissues Provides Useful Insights into Porcine Genome Annotation

Alternative splicing (AS) is a process during gene expression that results in a single gene coding for different protein variants. AS contributes to transcriptome and proteome diversity. In order to characterize AS in pigs, genome-wide transcripts and AS events were detected using RNA sequencing of 34 different tissues in Duroc pigs. In total, 138,403 AS events and 29,270 expressed genes were identified. An alternative donor site was the most common AS form and accounted for 44% of the total AS events. The percentage of the other three AS forms (exon skipping, alternative acceptor site, and intron retention) was approximately 19%. The results showed that the most common AS events involving alternative donor sites could produce different transcripts or proteins that affect the biological processes. The expression of genes with tissue-specific AS events showed that gene functions were consistent with tissue functions. AS increased proteome diversity and resulted in novel proteins that gained or lost important functional domains. In summary, these findings extend porcine genome annotation and highlight roles that AS could play in determining tissue identity.

Generation of Artificial Gamete and Embryo From Stem Cells in Reproductive Medicine

In addition to the great growing need for assisted reproduction technologies (ART), additional solutions for patients without functional gametes are strongly needed. Due to ethical restrictions, limited studies can be performed on human gametes and embryos; however, artificial gametes and embryos represent a new hope for clinical application and basic research in the field of reproductive medicine. Here, we provide a review of the research progress and possible application of artificial gametes and embryos from different species, including mice, monkeys and humans. Gametes specification from adult stem cells and embryonic stem cells (ESCs) as well as propagation of stem cells from the reproductive system and from organized embryos, which are similar to blastocysts, have been realized in some nonhuman mammals, but not all achievements can be replicated in humans. This area of research remains noteworthy and requires further study and effort to achieve the reconstitution of the entire cycle of gametogenesis and embryo development in vitro.

Changing Technologies of RNA Sequencing and Their Applications in Clinical Oncology

RNA sequencing (RNAseq) is one of the most commonly used techniques in life sciences, and has been widely used in cancer research, drug development, and cancer diagnosis and prognosis. Driven by various biological and technical questions, the techniques of RNAseq have progressed rapidly from bulk RNAseq, laser-captured micro-dissected RNAseq, and single-cell RNAseq to digital spatial RNA profiling, spatial transcriptomics, and direct in situ sequencing. These different technologies have their unique strengths, weaknesses, and suitable applications in the field of clinical oncology. To guide cancer researchers to select the most appropriate RNAseq technique for their biological questions, we will discuss each of these technologies, technical features, and clinical applications in cancer. We will help cancer researchers to understand the key differences of these RNAseq technologies and their optimal applications.

RASflow: an RNA-Seq analysis workflow with Snakemake

BACKGROUND

With the cost of DNA sequencing decreasing, increasing amounts of RNA-Seq data are being generated giving novel insight into gene expression and regulation. Prior to analysis of gene expression, the RNA-Seq data has to be processed through a number of steps resulting in a quantification of expression of each gene/transcript in each of the analyzed samples. A number of workflows are available to help researchers perform these steps on their own data, or on public data to take advantage of novel software or reference data in data re-analysis. However, many of the existing workflows are limited to specific types of studies. We therefore aimed to develop a maximally general workflow, applicable to a wide range of data and analysis approaches and at the same time support research on both model and non-model organisms. Furthermore, we aimed to make the workflow usable also for users with limited programming skills.

RESULTS

Utilizing the workflow management system Snakemake and the package management system Conda, we have developed a modular, flexible and user-friendly RNA-Seq analysis workflow: RNA-Seq Analysis Snakemake Workflow (RASflow). Utilizing Snakemake and Conda alleviates challenges with library dependencies and version conflicts and also supports reproducibility. To be applicable for a wide variety of applications, RASflow supports the mapping of reads to both genomic and transcriptomic assemblies. RASflow has a broad range of potential users: it can be applied by researchers interested in any organism and since it requires no programming skills, it can be used by researchers with different backgrounds. The source code of RASflow is available on GitHub: https://github.com/zhxiaokang/RASflow.

CONCLUSIONS

RASflow is a simple and reliable RNA-Seq analysis workflow covering many use cases.

Differential Alternative Splicing Genes in Response to Boron Deficiency in Brassica napus

Alternative splicing (AS) can increase transcriptome diversity, protein diversity and protein yield, and is an important mechanism to regulate plant responses to stress. Oilseed rape (Brassica napus L.), one of the main oil crops in China, shows higher sensitivity to boron (B) deficiency than other species. Here, we demonstrated AS changes that largely increased the diversity of the mRNA expressed in response to B deficiency in B. napus. Each gene had two or more transcripts on average. A total of 33.3% genes in both Qingyou10 (QY10, B-efficient cultivar) and Westar10 (W10, B-inefficient cultivar) showed AS in both B conditions. The types of AS events were mainly intron retention, 3′ alternative splice site, 5′ alternative splice site and exon skipping. The tolerance ability of QY10 was higher than that of W10, possibly because there were far more differential alternative splicing (DAS) genes identified in QY10 at low B conditions than in W10. The number of genes with both DAS and differentially expressed (DE) was far lower than that of the genes that were either with DAS or DE in QY10 and W10, suggesting that the DAS and DE genes were independent. Four Serine/Arginine-rich (SR) splicing factors, BnaC06g14780D, BnaA01g14750D, BnaA06g15930D and BnaC01g41640D, underwent differentially alternative splicing in both cultivars. There existed gene–gene interactions between BnaC06g14780D and the genes associated with the function of B in oilseed rape at low B supply. This suggests that oilseed rape could regulate the alterative pre-mRNA splicing of SR protein related genes to increase the plant tolerance to B deficiency.

De novo sequencing and transcriptome assembly of Arisaema heterophyllum Blume and identification of genes involved in isoflavonoid biosynthesis

Arisaema heterophyllum Blume (AhBl) is one of the valued medicinal plants. However, its genetic information is limited, which impedes further studies of this valuable resource. To investigate the genes involved in the isoflavonoid biosynthesis, we deeply performed transcriptome sequencing for AhBl. An average of 10.98 Gb clean reads were obtained based on root, tuber and leaf tissues, and 109,937 unigenes were yielded after de novo assembly. In total, 72,287 of those unigenes were annotated in at least one public database. The numbers of expressed unigenes in each tissue were 35,686, 43,363 and 47,783, respectively. The overall expression levels of transcripts in leaf were higher than those in root and tuber. Differentially expressed genes analysis indicated that a total of 12,448 shared unigenes were detected in all three tissues, 10,215 of which were higher expressed in tuber than that in root and leaf. Besides, 87 candidate unigenes that encode for enzymes involved in biosynthesis of isoflavonoid were identified and analyzed, and some key enzyme genes were experimentally validated by quantitative Real-Time PCR (qRT-PCR). This study provides a unique dataset for the systematic analysis of AhBl functional genes and expression characteristics, and facilitates the future study of the pharmacological mechanism of AhBl.

Acute Toxoplasma Gondii Infection in Cats Induced Tissue-Specific Transcriptional Response Dominated by Immune Signatures

RNA-sequencing was used to detect transcriptional changes in six tissues of cats, seven days after T. gondii infection. A total of 737 genes were differentially expressed (DEGs), of which 410 were up-regulated and 327 were down-regulated. The liver exhibited 151 DEGs, lung (149 DEGs), small intestine (130 DEGs), heart (123 DEGs), brain (104 DEGs), and spleen (80 DEGs)-suggesting tissue-specific transcriptional patterns. Gene ontology and KEGG analyses identified DEGs enriched in immune pathways, such as cytokine-cytokine receptor interaction, Jak-STAT signaling pathway, NOD-like receptor signaling pathway, NF-kappa B signaling pathway, MAPK signaling pathway, T cell receptor signaling pathway, and the cytosolic DNA sensing pathway. C-X-C motif chemokine 10 (CXCL10) was involved in most of the immune-related pathways. PI3K/Akt expression was down-regulated in all tissues, except the spleen. The genes for phosphatase, indoleamine 2,3-dioxygenase, Hes Family BHLH Transcription Factor 1, and guanylate-binding protein 5, playing various roles in immune defense, were co-expressed across various feline tissues. Multivariate K-means clustering analysis produced seven gene clusters featuring similar gene expression patterns specific to individual tissues, with lung tissue cluster having the largest number of DEGs. These findings suggest the presence of a broad immune defense mechanism across various tissues in cats against acute T. gondii infection.

Transcriptome analysis of the Yesso scallop, Patinopecten yessoensis gills in response to water temperature fluctuations

Water temperature fluctuations are considered to be a major factor affecting the immune functions and metabolic processes of scallops. To better understand the immune defense mechanisms of Yesso scallop, Patinopecten yessoensis following exposure to water temperature fluctuations, transcriptomic profiles in the gills from high-frequency fluctuations (HF_G), low-frequency fluctuations (LF_G), and no fluctuations (NF_G) groups were obtained using HiSeq™ 2500 (Illumina). For HF_G, scallops were transferred directly between 18 and 8 °C every 4 h and for 10 fluctuations, while scallops in LF_G were transferred between 18 and 13 °C every 12 h, for a total of 4 fluctuations. A total of 442,922,590 clean reads were generated in 9 libraries and then assembled into 210,780 unigenes with an average length of 705 bp and an N50 of 1253 bp. Based on sequence similarity, 54,529 unigenes (25.87%) were annotated in at least one database. Comparative analysis revealed that 696 unigenes differentially expressed in temperature stressed groups compared with the control, including 229 unigenes between HF_G and NF_G, and 548 unigenes between LF_G and NF_G, respectively. Additionally, among these differentially expressed genes (DEGs), there were 41 immune-related unigenes and 16 protein metabolism-related unigenes. These results provide fundamental information on the molecular defense mechanisms in the Yesso scallop gills after exposure to water temperature fluctuations.

Computational functional genomics-based approaches in analgesic drug discovery and repurposing

Persistent pain is a major healthcare problem affecting a fifth of adults worldwide with still limited treatment options. The search for new analgesics increasingly includes the novel research area of functional genomics, which combines data derived from various processes related to DNA sequence, gene expression or protein function and uses advanced methods of data mining and knowledge discovery with the goal of understanding the relationship between the genome and the phenotype. Its use in drug discovery and repurposing for analgesic indications has so far been performed using knowledge discovery in gene function and drug target-related databases; next-generation sequencing; and functional proteomics-based approaches. Here, we discuss recent efforts in functional genomics-based approaches to analgesic drug discovery and repurposing and highlight the potential of computational functional genomics in this field including a demonstration of the workflow using a novel R library ‘dbtORA’.

Genome-wide Analysis of Alternative Splicing in An Inbred Cabbage (Brassica oleracea L.) Line 'HO' in Response to Heat Stress

Introduction:

High-throughput RNA sequencing (RNA-Seq) studies demonstrate that Alter-native Splicing (AS) is a widespread mechanism that enhances transcriptome diversity, particularly in plants exposed to environmental stress. In an attempt to determine the transcriptome and AS patterns of cabbage inbred line “HO” under Heat Stress (HS), RNA-Seq was carried out using HS-treated and con-trol samples. Genome-wide analysis indicated that AS is differentially regulated in response to HS. The number of AS events markedly increased in HS-treated samples compared to the control.

Conclusion:

We identified 1,864 genes, including Heat shock transcription factor (Hsf) and heat shock protein (Hsp) genes, that exhibited >4-fold changes in expression upon exposure to HS. The enriched Gene Ontology (GO) terms of the 1,864 genes included ‘response to stress/abiotic stimulus/chemical stimulus’, among, which the genes most highly induced by HS encode small Hsps and Hsf proteins. The heat-induced genes also showed an increased number of AS events under HS conditions. In addi-tion, the distribution of AS types was altered under HS conditions, as the level of Intron Retention (IR) decreased, whereas other types of AS increased, under these conditions. Severe HS-induced AS was al-so observed in Hsfs and Hsps, which play crucial roles in regulating heat tolerance. Our results support the notion that AS of HS-related genes, such as HsfA2 and HsfB2a, are important for heat stress adapta-tion in cabbage.

Discovery of a new mechanism for regulation of plant triacylglycerol metabolism: The peanut diacylglycerol acyltransferase-1 gene family transcriptome is highly enriched in alternative splicing variants

Triacylglycerols (TAGs) are the most important energy storage form in oilseed crops. Diacylglycerol acyltransferase (DGAT) catalyzes the rate-limiting step of the Kennedy pathway of TAG biosynthesis. To date, little is known about the regulation of DGAT activity in peanut (Arachis hypogaea), an agronomically important oilseed crop that is cultivated in many parts of the world. In this study, seven distinct forms of type 1 DGAT (AhDGAT1.1-AhDGAT1.7) were identified, cloned, and characterized. Comparisons of the nucleotide sequences and gene structures revealed many different splicing variants of AhDGAT1, some of which displayed different organ-specific expression patterns. A representative gene (AhDGAT1.1) was transformed into wild-type tobacco and was shown to increase seed fatty acid (FA) content by 14.7%-20.9%. All seven AhDGAT1s were expressed in TAG-deficient Saccharomyces cerevisiae strain H1246; the five longest AhDGAT1 variants generated high levels of acyltransferase activity and complemented the free fatty acid lethality phenotype in this strain. The alternative splicing that gives rise to AhDGAT1.2 and AhDGAT1.4 creates predicted protein C-terminal truncations. The proteins encoded by these two variants were not active and did not complement the fatty acid sensitivity in H1246. These results were verified by visualization of intracellular lipid droplets using Nile Red staining. Collectively, the results presented here represent the first comprehensive analysis of the peanut DGAT1 gene family, which, unlike in other published plant DGAT1 sequences, shows widespread alternative splicing that may affect the expression patterns and enzyme activities of some members of the gene family.