Trimming of sequence reads alters RNA-Seq gene expression estimates

Transcriptomic signatures related to the immune priming of Ruditapes philippinarum in response to the re-infection of Vibrio anguillarum

Manila clam (Ruditapes philippinarum) is a commercially valuable bivalve species, but its susceptibility to pathogenic microorganisms in aquaculture limits the development of the shellfish industry. Immune priming has been previously found in other invertebrates, but not in the unique immune system of the R. philippinarum. In the present study, the survival rate of R. philippinarum after two consecutive injections of Vibrio anguillarum was recorded, and the mechanisms of immune priming was studied by transcriptome analysis of R. philippinarum after two consecutive stimulations of V. anguillarum. R. philippinarum was first injected with V. anguillarum with PBS control group (SA), and then injected with V. anguillarum again after seven days (AA) with PBS control group (SS). The log-rank test showed that the survival rate of the AA group after the second injection was significantly higher than that of the other control groups (P < 0.05). The analysis of hepatopancreatic bacterial load showed that the pathogen clearance efficiency of the AA group was significantly enhanced. The activities of alkaline phosphatase (AKP), acid phosphatase (ACP), antioxidant enzymes (SOD) and malondialdehyde (MDA) were significantly increased after V. anguillarum infection, and the secondary stimulation was significantly higher than the primary stimulation. In addition, transcriptome analysis results showed that a common 84 differentially expressed genes (DEGs) were up-regulated after the primary stimulation and secondary stimulation compared with the SS control group, including C-type mannose receptor 2 (MRC2), Ubiquitin-like protein ATG12 (Atg12) and Toll-like receptor 4 (TLR4). The results of transcriptome analysis were verified by qRT-PCR of fifteen immune-related DEGs. The results showed that the pattern recognition receptors (PRR)-related genes are involved in immune priming. This study provides novel insights into physiological and molecular evidences of the immune priming response in R. philippinarum.

Inflammatory cytokine upd3 induces axon length-dependent synapse removal by glia

Many neurodegenerative disorders (NDDs) preferentially affect neurons with long or complex axonal arbors but the cellular and molecular bases for neurite length-dependent vulnerability of neurons to degeneration is largely unknown. Using Drosophila sensory neurons as a model system we show that neuronal activation of the integrated stress response triggers expression of the Interleukin-6 homolog unpaired 3 (upd3), which is both necessary and sufficient for axon length-dependent degeneration of presynapses. Upd3 activates phagocytic glia, triggering phagocytic removal of presynapses preferentially on neurons with long axons, thus revealing an intrinsic axon length-dependent vulnerability to glial insult. Finally, we found that axon length-dependent presynapse loss in fly models of human NDDs utilized this pathway, requiring upd3 and glial expression of the phagocytic receptor draper. Our studies identify inflammatory cytokine signaling and glial phagocytosis as key determinants of axon length-dependent vulnerability, thus mechanistically linking these hallmarks of NDDs.

Transcriptomic analysis of CDL-gated photoperiodic flowering mechanisms in cannabis and their responsiveness to R: FR ratios in controlled environment agriculture

While discrete regulatory mechanisms have been identified, a unified model for the transcriptional activation of photoperiodic flowering in short-day (SD) plants has not been delineated. Although the GIGANTEA-CONSTANS-FLOWERING LOCUS T (GI-CO-FT) pathway appears to be highly conserved, each species may differ in its blueprint for activation of FT and floral meristem identity. In cannabis, an SD plant, PSEUDO-RESPONSE-REGULATOR 37 (PRR37) has a causal effect in determining photoperiod sensitivity. This study identifies a network of WITH NO LYSINE (K) kinases (WNK) which may be regulating the PRR proteins and downstream genes, including florigen (FT). CO-like genes have been identified in cannabis, but their function in regulating FT has not been determined. This study shows that in cannabis, CO is critically-day-length-gated (CDL) and down-regulated by short days, likely to act as a repressor of FT. We demonstrate that CDL-gated gene expression can be manipulated in cannabis horticulture through modifying the R:FR ratio of LED lighting, where increased expression of COL5 in response to light treatment is inversely related with expression of FT. Building on these insights, we propose a model for the CDL-gated regulation of FT expression in cannabis.

Drosophila epidermal cells are intrinsically mechanosensitive and modulate nociceptive behavioral outputs

Somatosensory neurons (SSNs) that detect and transduce mechanical, thermal, and chemical stimuli densely innervate an animal's skin. However, although epidermal cells provide the first point of contact for sensory stimuli, our understanding of roles that epidermal cells play in SSN function, particularly nociception, remains limited. Here, we show that stimulating Drosophila epidermal cells elicits activation of SSNs including nociceptors and triggers a variety of behavior outputs, including avoidance and escape. Further, we find that epidermal cells are intrinsically mechanosensitive and that epidermal mechanically evoked calcium responses require the store-operated calcium channel Orai. Epidermal cell stimulation augments larval responses to acute nociceptive stimuli and promotes prolonged hypersensitivity to subsequent mechanical stimuli. Hence, epidermal cells are key determinants of nociceptive sensitivity and sensitization, acting as primary sensors of noxious stimuli that tune nociceptor output and drive protective behaviors.

Building better genome annotations across the tree of life

Recent technological advances in long-read DNA sequencing accompanied by reduction in costs have made the production of genome assemblies financially achievable and computationally feasible, such that genome assembly no longer represents the major hurdle to evolutionary analysis for most nonmodel organisms. Now, the more difficult challenge is to properly annotate a draft genome assembly once it has been constructed. The primary challenge to annotations is how to select from the myriad gene prediction tools that are currently available, determine what kinds of data are necessary to generate high-quality annotations, and evaluate the quality of the annotation. To determine which methods perform the best and to determine whether the inclusion of RNA-seq data is necessary to obtain a high-quality annotation, we generated annotations with 12 different methods for 21 different species spanning vertebrates, plants, and insects. We found that the annotation transfer method TOGA, BRAKER3, and the RNA-seq assembler StringTie were consistently top performers across a variety of metrics including BUSCO recovery, CDS length, and false-positive rate, with the exception that TOGA performed less well in some monocots with respect to BUSCO recovery. The choice of which of the top-performing methods will depend upon the feasibility of whole-genome alignment, availability of RNA-seq data, importance of capturing noncoding parts of the transcriptome, and, when whole-genome alignment is not feasible, the relative performance in BUSCO recovery between BRAKER3 and StringTie. When whole-genome alignment is not feasible, inclusion of RNA-seq data will lead to substantial improvements to genome annotations.

Effects of water-accommodated fractions of crude oil on detoxification and antioxidant mechanisms in Ruditapes philippinarum

To assess the impact of crude oil pollution on Manila clams (Ruditapes philippinarum), we analyzed the effects of exposure to water-accommodated fraction (WAF) at different concentrations (nominal TPH concentrations of 0.5, 1.0 and 3.0 mg/L), including survival rate, histopathology observation and antioxidant enzyme detection. Results demonstrated that the activities of antioxidant enzymes-Catalase (CAT), Superoxide dismutase (SOD), Glutathione peroxidase (GSH-PX) and Malondialdehyde (MDA) in Manila clams was significantly elevated in 3.0 mg/L WAF group compared with the control group (P < 0.05). In addition, RNA-seq was performed to analyze clam hepatopancreas tissue in 0 d (control group, CG), 7 d (exposure group, O7d), 15 d (exposure group, O15d) after the exposure to WAF (3 mg/L) and recovery in clean water for 7 d after 15 d WAF exposure (recovery group, R7d). The results showed that a total of 129 differentially expressed genes (DEGs) were detected in the O7d vs CG group, 123 DEGs were detected in the O15d vs CG group, and 2113 DEGs were detected in the R7d vs CG group. Of these genes, the expression of cytochrome P450 2J2 (6.30-fold), bile salt sulfotransferase (8.06-fold), multidrug resistance-associated protein 1 (8.17-fold) was significantly induced at 15 d under the WAF exposure. DEGs were significantly enriched in pathways such as cysteine and methionine metabolism, as well as glycine, serine and threonine metabolism. Furthermore, eight DEGs, including metabolism-related genes (ABCC1, ABCG2, SULT2A1, CYP2J2), ion transport genes (SLC39a14, RFT2), an immune-related gene (Gvin1), and a cellular structure and signal regulatory gene (Ank3) were selected for qRT-PCR analysis. The results confirmed that DEG expression levels were consistent with RNA-seq findings. This study provides crucial molecular insights into the adaptive responses and recovery processes of marine bivalves in response to oil pollution, thereby contributing a scientific foundation for evaluating and monitoring marine environmental pollution.

Analysis of the Pattern of RNA Expression in the Skin of TR-Deficient Mice By RNA-seq

RNA-sequencing (RNA-seq) has become the method of choice for whole transcriptome analysis, as it enables profiling of a wide range of RNA molecules and the always evolving bioinformatic pipelines allow the extraction of diverse biological information from a single sample. However, there is not a gold-standard RNA-seq protocol nor an optimal bioinformatic pipeline defined, which can challenge new users. The aim of this chapter is to describe the basic RNA-sequencing pipeline, from RNA extraction and library preparation to the bioinformatic preprocessing and downstream analyses. The steps are oriented to the transcriptome analysis of the skin of TR-deficient mice, but the protocol can be easily translated to other tissue types or organisms.

Pharmacokinetics and cardioprotective efficacy of intravenous miR-125b* microRNA mimic in a mouse model of acute myocardial infarction

BACKGROUND AND PURPOSE

MicroRNA (miRNA) therapy is a promising approach to induce cardioprotection. We have previously identified cardiac microRNA-125b* (microRNA-125b-2-3p; miR-125b*) as a potential cardioprotective miRNA, termed ProtectomiR. We aimed to characterize the pharmacokinetics and pharmacodynamics, and the effect of miR-125b* mimic on infarct size using an in vivo mouse model.

EXPERIMENTAL APPROACH

To characterize the pharmacokinetics properties of miR-125b* mimic, a single injection of 10-μg miR-125b* mimic or its scramble miRNA control, or vehicle i.v. was given to C57BL/6 mice. MiR-125b* expression was measured from plasma, heart, kidney and liver samples. Effect of miR-125b* on area at risk and infarct size was assessed after 45-min coronary occlusion, followed by 24-h reperfusion; 10-μg miR-125b* mimic or 10-μg non-targeting miRNA mimic control or vehicle were administered via the right jugular vein at 10th mins of coronary occlusion. To assess molecular mechanism involved in cardioprotection, expression of mRNA targets of miR-125b* were measured from ventricular myocardium at 1, 2, 4, 8 or 24 h post-treatment using quantitative real time polymerase chain reaction.

KEY RESULTS

MiR-125b* expression was markedly increased in plasma and myocardium 1 h, and in the liver 2h after treatment. Infarct size was significantly reduced after miR-125b* mimic treatment when compared to the vehicle. The expression of Ccna2, Eef2k and Cacnb2 target mRNAs was significantly reduced 8 h after injection of miR-125b* mimic.

CONCLUSION AND IMPLICATIONS

This is the first demonstration of pharmacokinetic and molecular pharmacodynamic properties as well as the cardioprotective effect of miR-125b* mimic in vivo.

LINKED ARTICLES

This article is part of a themed issue Non-coding RNA Therapeutics. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v182.2/issuetoc.

Large-scale proteogenomics characterization of microproteins in Mycobacterium tuberculosis

Tuberculosis remains a burden to this day, due to the rise of multi and extensively drug-resistant bacterial strains. The genome of Mycobacterium tuberculosis (Mtb) strain H37Rv underwent an annotation process that excluded small Open Reading Frames (smORFs), which encode a class of peptides and small proteins collectively known as microproteins. As a result, there is an overlooked part of its proteome that is a rich source of potentially essential, druggable molecular targets. Here, we employed our recently developed proteogenomics pipeline to identify novel microproteins encoded by non-canonical smORFs in the genome of Mtb using hundreds of mass spectrometry experiments in a large-scale approach. We found protein evidence for hundreds of unannotated microproteins and identified smORFs essential for bacterial survival and involved in bacterial growth and virulence. Moreover, many smORFs are co-expressed and share operons with a myriad of biologically relevant genes and play a role in antibiotic response. Together, our data presents a resource of unknown genes that play a role in the success of Mtb as a widespread pathogen.

Enhanced expression of the myogenic factor Myocyte enhancer factor-2 in imaginal disc myoblasts activates a partial, but incomplete, muscle development program

The Myocyte enhancer factor-2 (MEF2) transcription factor plays a vital role in orchestrating muscle differentiation. While MEF2 cannot effectively induce myogenesis in naïve cells, it can potently accelerate myogenesis in mesodermal cells. This includes in Drosophila melanogaster imaginal disc myoblasts, where triggering premature muscle gene expression in these adult muscle progenitors has become a paradigm for understanding the regulation of the myogenic program. Here, we investigated the global consequences of MEF2 overexpression in the imaginal wing disc myoblasts, by combining RNA-sequencing with RT-qPCR and immunofluorescence. We observed the formation of sarcomere-like structures that contained both muscle and cytoplasmic myosin, and significant upregulation of muscle gene expression, especially genes essential for myofibril formation and function. These transcripts were functional since numerous myofibrillar proteins were detected in discs using immunofluorescence. Interestingly, muscle genes whose expression is restricted to the adult stages were not activated in these adult myoblasts. These studies confirm a broad activation of the myogenic program in response to MEF2 expression and suggest that additional regulatory factors are required for promoting the adult muscle-specific program. Our findings contribute to understanding the regulatory mechanisms governing muscle development and highlight the multifaceted role of MEF2 in orchestrating this intricate process.

AI-enabled pipeline for virus detection, validation, and SNP discovery from next-generation sequencing data

Background and Aims

The rapid and accurate detection of viruses and the discovery of single nucleotide polymorphisms (SNPs) are critical for disease management and understanding viral evolution. This study presents a pipeline for virus detection, validation, and SNP discovery from next-generation sequencing (NGS) data. The pipeline processes raw sequencing data to identify viral sequences with high accuracy and sensitivity by integrating state-of-the-art bioinformatics tools with artificial intelligence.

Methods

Before aligning the reads to the reference genomes, quality control measures, and adapter trimming are performed to ensure the integrity of the data. Unmapped reads are subjected to de novo assembly to reveal novel viral sequences and genetic elements.

Results

The effectiveness of the pipeline is demonstrated by the identification of virus sequences, illustrating its potential for detecting known and emerging pathogens. SNP discovery is performed using a custom Python script that compares the entire population of sequenced viral reads to a reference genome. This approach provides a comprehensive overview of viral genetic diversity and identifies dominant variants and a spectrum of genetic variations.

Conclusion

The robustness of the pipeline is confirmed by the recovery of complete viral sequences, which improves our understanding of viral genomics. This research aims to develop an auto-bioinformatics pipeline for novel viral sequence discovery, in vitro validation, and SNPs using the Python (AI) language to understand viral evolution. This study highlights the synergy between traditional bioinformatics techniques and modern approaches, providing a robust tool for analyzing viral genomes and contributing to the broader field of viral genomics.

Protective Effects of Keratinocyte-Derived GCSF and CCL20 on UVB-Induced Melanocyte Damage

The skin microenvironment created by keratinocytes (KC) influences the stress responses of melanocytes (MC) to UVB insults. This study employed RNA sequencing analysis as well as in vitro and in vivo models to elucidate the underlying mechanisms. Our RNA-Seq analysis revealed a statistically significant upregulation of GCSF and CCL20 genes in UVB-irradiated KC, correlating with the protective effects of KC on MC responses to UVB exposure. Recombinant GCSF and CCL20 exhibited the most pronounced modulation of UVB-induced MC responses. These effects included the attenuation of apoptosis and reduction of ROS formation, along with the upregulation of tyrosinase and tyrosinase-related protein-1, which are involved in the melanogenic pathway. ELISA was also used to confirm that UVB could induce the secretion of GCSF and CCL20 from KC. A similar correlation between GCSF and CCL20 expression in KC and tyrosinase levels in MC was observed in UVB-irradiated mouse skin. Our study provides novel insights into the protective role of GCSF and CCL20 in the paracrine effects of KC on UVB-induced MC damage through the modulation of stress response pathways, the MITF-tyrosinase axis, and the regulation of p53. These findings have implications for the development of pharmacological strategies targeting KC-derived paracrine factors for the prevention of skin photodamage.

Clinical relevance and therapeutic predictive ability of hypoxia biomarkers in head and neck cancer tumour models

Tumour hypoxia promotes poor patient outcomes, with particularly strong evidence for head and neck squamous cell carcinoma (HNSCC). To effectively target hypoxia, therapies require selection biomarkers and preclinical models that can accurately model tumour hypoxia. We established 20 patient-derived xenograft (PDX) and cell line-derived xenograft (CDX) models of HNSCC that we characterised for their fidelity to represent clinical HNSCC in gene expression, hypoxia status and proliferation and that were evaluated for their sensitivity to hypoxia-activated prodrugs (HAPs). PDX models showed greater fidelity in gene expression to clinical HNSCC than cell lines, as did CDX models relative to their paired cell lines. PDX models were significantly more hypoxic than CDX models, as assessed by hypoxia gene signatures and pimonidazole immunohistochemistry, and showed similar hypoxia gene expression to clinical HNSCC tumours. Hypoxia or proliferation status alone could not determine HAP sensitivity across our 20 HNSCC and two non-HNSCC tumour models by either tumour growth inhibition or killing of hypoxia cells in an ex vivo clonogenic assay. In summary, our tumour models provide clinically relevant HNSCC models that are suitable for evaluating hypoxia-targeting therapies; however, additional biomarkers to hypoxia are required to accurately predict drug sensitivity.

A comprehensive workflow for optimizing RNA-seq data analysis

BACKGROUND

Current RNA-seq analysis software for RNA-seq data tends to use similar parameters across different species without considering species-specific differences. However, the suitability and accuracy of these tools may vary when analyzing data from different species, such as humans, animals, plants, fungi, and bacteria. For most laboratory researchers lacking a background in information science, determining how to construct an analysis workflow that meets their specific needs from the array of complex analytical tools available poses a significant challenge.

RESULTS

By utilizing RNA-seq data from plants, animals, and fungi, it was observed that different analytical tools demonstrate some variations in performance when applied to different species. A comprehensive experiment was conducted specifically for analyzing plant pathogenic fungal data, focusing on differential gene analysis as the ultimate goal. In this study, 288 pipelines using different tools were applied to analyze five fungal RNA-seq datasets, and the performance of their results was evaluated based on simulation. This led to the establishment of a relatively universal and superior fungal RNA-seq analysis pipeline that can serve as a reference, and certain standards for selecting analysis tools were derived for reference. Additionally, we compared various tools for alternative splicing analysis. The results based on simulated data indicated that rMATS remained the optimal choice, although consideration could be given to supplementing with tools such as SpliceWiz.

CONCLUSION

The experimental results demonstrate that, in comparison to the default software parameter configurations, the analysis combination results after tuning can provide more accurate biological insights. It is beneficial to carefully select suitable analysis software based on the data, rather than indiscriminately choosing tools, in order to achieve high-quality analysis results more efficiently.

Transcriptome analysis provides new insights into the immune response of Ruditapes philippinarum infected with Vibrio alginolyticus

Manila clam (Ruditapes philippinarum) is a bivalve species with commercial value, but it is easily infected by pathogenic microorganisms in aquaculture, which restricts the shellfish industry. Notably, the impact of Vibrio alginolyticus on clam culture is obvious. In this study, RNA-seq was performed to analyze clam hepatopancreas tissue in 48 h (challenge group, G48h) and 96 h (challenge group, G96h) after infection with V. alginolyticus and 0 h after injection of PBS (control group, C). The results showed that a total of 1670 differentially expressed genes were detected in the G48h vs C group, and 1427 differentially expressed genes were detected in the G96h vs C group. In addition, KEGG analysis showed that DEGs were significantly enriched in pathways such as Lysosome and Mitophagy. Moreover, 15 immune related DEGs were selected for qRT-PCR analysis to verify the accuracy of RNA-seq, and the results showed that the expression level of DEGs was consistent with that of RNA-seq. Therefore, the results obtained in this study provides a preliminary understanding of the immune defense of R. philippinarum and molecular insights for genetic breeding of V. alginolyticus resistance in Manila clam.

Single-cell profiling reveals transcriptome dynamics during bovine oocyte growth

BACKGROUND

Mammalian follicle development is characterized by extensive changes in morphology, endocrine responsiveness, and function, providing the optimum environment for oocyte growth, development, and resumption of meiosis. In cattle, the first signs of transcription activation in the oocyte are observed in the secondary follicle, later than during mouse and human oogenesis. While many studies have generated extensive datasets characterizing gene expression in bovine oocytes, they are mostly limited to the analysis of fully grown and matured oocytes. The aim of the present study was to apply single-cell RNA sequencing to interrogate the transcriptome of the growing bovine oocyte from the secondary follicle stage through to the mid-antral follicle stage.

RESULTS

Single-cell RNA-seq libraries were generated from oocytes of known diameters (< 60 to > 120 μm), and datasets were binned into non-overlapping size groups for downstream analysis. Combining the results of weighted gene co-expression network and Trendy analyses, and differently expressed genes (DEGs) between size groups, we identified a decrease in oxidative phosphorylation and an increase in maternal -genes and transcription regulators across the bovine oocyte growth phase. In addition, around 5,000 genes did not change in expression, revealing a cohort of stable genes. An interesting switch in gene expression profile was noted in oocytes greater than 100 μm in diameter, when the expression of genes related to cytoplasmic activities was replaced by genes related to nuclear activities (e.g., chromosome segregation). The highest number of DEGs were detected in the comparison of oocytes 100-109 versus 110-119 μm in diameter, revealing a profound change in the molecular profile of oocytes at the end of their growth phase.

CONCLUSIONS

The current study provides a unique dataset of the key genes and pathways characteristic of each stage of oocyte development, contributing an important resource for a greater understanding of bovine oogenesis.

Dendrite intercalation between epidermal cells tunes nociceptor sensitivity to mechanical stimuli in Drosophila larvae

An animal's skin provides a first point of contact with the sensory environment, including noxious cues that elicit protective behavioral responses. Nociceptive somatosensory neurons densely innervate and intimately interact with epidermal cells to receive these cues, however the mechanisms by which epidermal interactions shape processing of noxious inputs is still poorly understood. Here, we identify a role for dendrite intercalation between epidermal cells in tuning sensitivity of Drosophila larvae to noxious mechanical stimuli. In wild-type larvae, dendrites of nociceptive class IV da neurons intercalate between epidermal cells at apodemes, which function as body wall muscle attachment sites, but not at other sites in the epidermis. From a genetic screen we identified miR-14 as a regulator of dendrite positioning in the epidermis: miR-14 is expressed broadly in the epidermis but not in apodemes, and miR-14 inactivation leads to excessive apical dendrite intercalation between epidermal cells. We found that miR-14 regulates expression and distribution of the epidermal Innexins ogre and Inx2 and that these epidermal gap junction proteins restrict epidermal dendrite intercalation. Finally, we found that altering the extent of epidermal dendrite intercalation had corresponding effects on nociception: increasing epidermal intercalation sensitized larvae to noxious mechanical inputs and increased mechanically evoked calcium responses in nociceptive neurons, whereas reducing epidermal dendrite intercalation had the opposite effects. Altogether, these studies identify epidermal dendrite intercalation as a mechanism for mechanical coupling of nociceptive neurons to the epidermis, with nociceptive sensitivity tuned by the extent of intercalation.

Machine learning on alignment features for parent-of-origin classification of simulated hybrid RNA-seq

BACKGROUND

Parent-of-origin allele-specific gene expression (ASE) can be detected in interspecies hybrids by virtue of RNA sequence variants between the parental haplotypes. ASE is detectable by differential expression analysis (DEA) applied to the counts of RNA-seq read pairs aligned to parental references, but aligners do not always choose the correct parental reference.

RESULTS

We used public data for species that are known to hybridize. We measured our ability to assign RNA-seq read pairs to their proper transcriptome or genome references. We tested software packages that assign each read pair to a reference position and found that they often favored the incorrect species reference. To address this problem, we introduce a post process that extracts alignment features and trains a random forest classifier to choose the better alignment. On each simulated hybrid dataset tested, our machine-learning post-processor achieved higher accuracy than the aligner by itself at choosing the correct parent-of-origin per RNA-seq read pair.

CONCLUSIONS

For the parent-of-origin classification of RNA-seq, machine learning can improve the accuracy of alignment-based methods. This approach could be useful for enhancing ASE detection in interspecies hybrids, though RNA-seq from real hybrids may present challenges not captured by our simulations. We believe this is the first application of machine learning to this problem domain.

Comprehensive RNA-sequencing analysis of colorectal cancer in a Korean cohort

Considering the recent increase in the number of colorectal cancer (CRC) cases in South Korea, we aimed to clarify the molecular characteristics of CRC unique to the Korean population. To gain insights into the complexities of CRC and promote the exchange of critical data, RNA-sequencing analysis was performed to reveal the molecular mechanisms that drive the development and progression of CRC; this analysis is critical for developing effective treatment strategies. We performed RNA-sequencing analysis of CRC and adjacent normal tissue samples from 214 Korean participants (comprising a total of 381 including 169 normal and 212 tumor samples) to investigate differential gene expression between the groups. We identified 19,575 genes expressed in CRC and normal tissues, with 3,830 differentially expressed genes (DEGs) between the groups. Functional annotation analysis revealed that the upregulated DEGs were significantly enriched in pathways related to the cell cycle, DNA replication, and IL-17, whereas the downregulated DEGs were enriched in metabolic pathways. We also analyzed the relationship between clinical information and subtypes using the Consensus Molecular Subtype (CMS) classification. Furthermore, we compared groups clustered within our dataset to CMS groups and performed additional analysis of the methylation data between DEGs and CMS groups to provide comprehensive biological insights from various perspectives. Our study provides valuable insights into the molecular mechanisms underlying CRC in Korean patients and serves as a platform for identifying potential target genes for this disease. The raw data and processed results have been deposited in a public repository for further analysis and exploration.

The genomes of Scedosporium between environmental challenges and opportunism

Emerging fungal pathogens are a global challenge for humankind. Many efforts have been made to understand the mechanisms underlying pathogenicity in bacteria, and OMICs techniques are largely responsible for those advancements. By contrast, our limited understanding of opportunism and antifungal resistance is preventing us from identifying, limiting and interpreting the emergence of fungal pathogens. The genus Scedosporium (Microascaceae) includes fungi with high tolerance to environmental pollution, whilst some species can be considered major human pathogens, such as Scedosporium apiospermum and Scedosporium boydii. However, unlike other fungal pathogens, little is known about the genome evolution of these organisms. We sequenced two novel genomes of Scedosporium aurantiacum and Scedosporium minutisporum isolated from extreme, strongly anthropized environments. We compared all the available Scedosporium and Microascaceae genomes, that we systematically annotated and characterized ex novo in most cases. The genomes in this family were integrated in a Phylum-level comparison to infer the presence of putative, shared genomic traits in filamentous ascomycetes with pathogenic potential. The analysis included the genomes of 100 environmental and clinical fungi, revealing poor evolutionary convergence of putative pathogenicity traits. By contrast, several features in Microascaceae and Scedosporium were detected that might have a dual role in responding to environmental challenges and allowing colonization of the human body, including chitin, melanin and other cell wall related genes, proteases, glutaredoxins and magnesium transporters. We found these gene families to be impacted by expansions, orthologous transposon insertions, and point mutations. With RNA-seq, we demonstrated that most of these anciently impacted genomic features responded to the stress imposed by an antifungal compound (voriconazole) in the two environmental strains S. aurantiacum MUT6114 and S. minutisporum MUT6113. Therefore, the present genomics and transcriptomics investigation stands on the edge between stress resistance and pathogenic potential, to elucidate whether fungi were pre-adapted to infect humans. We highlight the strengths and limitations of genomics applied to opportunistic human pathogens, the multifactoriality of pathogenicity and resistance to drugs, and suggest a scenario where pressures other than anthropic contributed to forge filamentous human pathogens.

Dendrite intercalation between epidermal cells tunes nociceptor sensitivity to mechanical stimuli in Drosophila larvae

An animal's skin provides a first point of contact with the sensory environment, including noxious cues that elicit protective behavioral responses. Nociceptive somatosensory neurons densely innervate and intimately interact with epidermal cells to receive these cues, however the mechanisms by which epidermal interactions shape processing of noxious inputs is still poorly understood. Here, we identify a role for dendrite intercalation between epidermal cells in tuning sensitivity of Drosophila larvae to noxious mechanical stimuli. In wild-type larvae, dendrites of nociceptive class IV da neurons intercalate between epidermal cells at apodemes, which function as body wall muscle attachment sites, but not at other sites in the epidermis. From a genetic screen we identified miR-14 as a regulator of dendrite positioning in the epidermis: miR-14 is expressed broadly in the epidermis but not in apodemes, and miR-14 inactivation leads to excessive apical dendrite intercalation between epidermal cells. We found that miR-14 regulates expression and distribution of the epidermal Innexins ogre and Inx2 and that these epidermal gap junction proteins restrict epidermal dendrite intercalation. Finally, we found that altering the extent of epidermal dendrite intercalation had corresponding effects on nociception: increasing epidermal intercalation sensitized larvae to noxious mechanical inputs and increased mechanically evoked calcium responses in nociceptive neurons, whereas reducing epidermal dendrite intercalation had the opposite effects. Altogether, these studies identify epidermal dendrite intercalation as a mechanism for mechanical coupling of nociceptive neurons to the epidermis, with nociceptive sensitivity tuned by the extent of intercalation.

Methods behind neoantigen prediction for personalized anticancer vaccines

Next to conventional cancer therapies, immunotherapies such as immune checkpoint inhibitors have broadened the cancer treatment landscape over the past decades. Recent advances in next generation sequencing and bioinformatics technologies have made it possible to identify a patient's own immunogenic neoantigens. These cancer neoantigens serve as important targets for personalized immunotherapy which has the benefit of being more active and effective in targeting cancer cells. This paper is a step-by-step guide discussing the different analyses and challenges encountered during in-silico neoantigen prediction. The protocol describes all the tools and steps required for the identification of immunogenic neoantigens.

Droplet Digital PCR Is a Novel Screening Method Identifying Potential Cardiac G-Protein-Coupled Receptors as Candidate Pharmacological Targets in a Rat Model of Pressure-Overload-Induced Cardiac Dysfunction

The identification of novel drug targets is needed to improve the outcomes of heart failure (HF). G-protein-coupled receptors (GPCRs) represent the largest family of targets for already approved drugs, thus providing an opportunity for drug repurposing. Here, we aimed (i) to investigate the differential expressions of 288 cardiac GPCRs via droplet digital PCR (ddPCR) and bulk RNA sequencing (RNAseq) in a rat model of left ventricular pressure-overload; (ii) to compare RNAseq findings with those of ddPCR; and (iii) to screen and test for novel, translatable GPCR drug targets in HF. Male Wistar rats subjected to transverse aortic constriction (TAC, n = 5) showed significant systolic dysfunction vs. sham operated animals (SHAM, n = 5) via echocardiography. In TAC vs. SHAM hearts, RNAseq identified 69, and ddPCR identified 27 significantly differentially expressed GPCR mRNAs, 8 of which were identified using both methods, thus showing a correlation between the two methods. Of these, Prostaglandin-F2α-receptor (Ptgfr) was further investigated and localized on cardiomyocytes and fibroblasts in murine hearts via RNA-Scope. Antagonizing Ptgfr via AL-8810 reverted angiotensin-II-induced cardiomyocyte hypertrophy in vitro. In conclusion, using ddPCR as a novel screening method, we were able to identify GPCR targets in HF. We also show that the antagonism of Ptgfr could be a novel target in HF by alleviating cardiomyocyte hypertrophy.

Environmental RNA as a Noninvasive Tool for Assessing Toxic Effects in Fish: A Proof-of-concept Study Using Japanese Medaka Exposed to Pyrene

Although environmental RNA (eRNA) is emerging as a noninvasive tool to assess the health status of aquatic macroorganisms, the potential of eRNA in assessing chemical hazards remain largely untested. In this study, we investigated the ability of eRNA to detect changes in gene expression in Japanese medaka fish (Oryzias latipes) in response to sublethal pyrene exposure, as a model toxic chemical. We performed standardized acute toxicity tests and collected eRNA from tank water and RNA from fish tissue after 96 h of exposure. Our results showed that over 1000 genes were detected in eRNA and the sequenced read counts of these genes correlated with those in fish tissue (r = 0.50). Moreover, eRNA detected 86 differentially expressed genes in response to pyrene, some of which were shared by fish RNA, including the suppression of collagen fiber genes. These results suggest that eRNA has the potential to detect changes in gene expression in fish in response to environmental stressors without the need for sacrificing or causing pain to fish. However, we also found that the majority of sequenced reads of eRNA (>99%) were not mapped to the reference medaka genome and they originated from bacteria and fungi, resulting in low sequencing depth. In addition, eRNA, in particular nuclear genes, was highly degraded with a median transcript integrity number (TIN) of <20. These limitations highlight the need for future studies to improve the analytical methods of eRNA application.

Design, execution, and interpretation of plant RNA-seq analyses

Genomics has transformed our understanding of the genetic architecture of traits and the genetic variation present in plants. Here, we present a review of how RNA-seq can be performed to tackle research challenges addressed by plant sciences. We discuss the importance of experimental design in RNA-seq, including considerations for sampling and replication, to avoid pitfalls and wasted resources. Approaches for processing RNA-seq data include quality control and counting features, and we describe common approaches and variations. Though differential gene expression analysis is the most common analysis of RNA-seq data, we review multiple methods for assessing gene expression, including detecting allele-specific gene expression and building co-expression networks. With the production of more RNA-seq data, strategies for integrating these data into genetic mapping pipelines is of increased interest. Finally, special considerations for RNA-seq analysis and interpretation in plants are needed, due to the high genome complexity common across plants. By incorporating informed decisions throughout an RNA-seq experiment, we can increase the knowledge gained.

Single-cell transcriptomics and data analyses for prokaryotes-Past, present and future concepts

Transcriptomics, or more specifically mRNA sequencing, is a powerful tool to study gene expression at the single-cell level (scRNA-seq) which enables new insights into a plethora of biological processes. While methods for single-cell RNA-seq in eukaryotes are well established, application to prokaryotes is still challenging. Reasons for that are rigid and diverse cell wall structures hampering lysis, the lack of polyadenylated transcripts impeding mRNA enrichment, and minute amounts of RNA requiring amplification steps before sequencing. Despite those obstacles, several promising scRNA-seq approaches for bacteria have been published recently, albeit difficulties in the experimental workflow and data processing and analysis remain. In particular, bias is often introduced by amplification which makes it difficult to distinguish between technical noise and biological variation. Future optimization of experimental procedures and data analysis algorithms are needed for the improvement of scRNA-seq but also to aid in the emergence of prokaryotic single-cell multi-omics. to help address 21st century challenges in the biotechnology and health sector.

Chromatin accessibility differences between alpha, beta, and delta cells identifies common and cell type-specific enhancers

BACKGROUND

High throughput sequencing has enabled the interrogation of the transcriptomic landscape of glucagon-secreting alpha cells, insulin-secreting beta cells, and somatostatin-secreting delta cells. These approaches have furthered our understanding of expression patterns that define healthy or diseased islet cell types and helped explicate some of the intricacies between major islet cell crosstalk and glucose regulation. All three endocrine cell types derive from a common pancreatic progenitor, yet alpha and beta cells have partially opposing functions, and delta cells modulate and control insulin and glucagon release. While gene expression signatures that define and maintain cellular identity have been widely explored, the underlying epigenetic components are incompletely characterized and understood. However, chromatin accessibility and remodeling is a dynamic attribute that plays a critical role to determine and maintain cellular identity.

RESULTS

Here, we compare and contrast the chromatin landscape between mouse alpha, beta, and delta cells using ATAC-Seq to evaluate the significant differences in chromatin accessibility. The similarities and differences in chromatin accessibility between these related islet endocrine cells help define their fate in support of their distinct functional roles. We identify patterns that suggest that both alpha and delta cells are poised, but repressed, from becoming beta-like. We also identify patterns in differentially enriched chromatin that have transcription factor motifs preferentially associated with different regions of the genome. Finally, we not only confirm and visualize previously discovered common endocrine- and cell specific- enhancer regions across differentially enriched chromatin, but identify novel regions as well. We compiled our chromatin accessibility data in a freely accessible database of common endocrine- and cell specific-enhancer regions that can be navigated with minimal bioinformatics expertise.

CONCLUSIONS

Both alpha and delta cells appear poised, but repressed, from becoming beta cells in murine pancreatic islets. These data broadly support earlier findings on the plasticity in identity of non-beta cells under certain circumstances. Furthermore, differential chromatin accessibility shows preferentially enriched distal-intergenic regions in beta cells, when compared to either alpha or delta cells.

Toxicity assessment of hexafluoropropylene oxide-dimer acid on morphology, heart physiology, and gene expression during zebrafish (Danio rerio) development

Hexafluoropropylene oxide-dimer acid (HFPO-DA) is one of the emerging replacements for the "forever" carcinogenic and toxic long-chain PFAS. HFPO-DA is a polymerization aid used for manufacturing fluoropolymers, whose global distribution and undetermined toxic properties are a concern regarding human and ecological health. To assess embryotoxic potential, zebrafish embryos were exposed to HFPO-DA at concentrations of 0.5-20,000 mg/L at 24-, 48-, and 72-h post-fertilization (hpf). Heart rate increased significantly in embryos exposed to 2 mg/L and 10 mg/L HFPO-DA across all time points. Spinal deformities and edema phenotypes were evident among embryos exposed to 1000-16,000 mg/L HFPO-DA at 72 hpf. A median lethal concentration (LC₅₀) was derived as 7651 mg/L at 72 hpf. Shallow RNA sequencing analysis of 9465 transcripts identified 38 consistently differentially expressed genes at 0.5 mg/L, 1 mg/L, 2 mg/L, and 10 mg/L HFPO-DA exposures. Notably, seven downregulated genes were associated with visual response, and seven upregulated genes were expressed in or regulated the cardiovascular system. This study identifies biological targets and molecular pathways affected during animal development by an emerging, potentially problematic, and ubiquitous industrial chemical.

Bulk and Single-Cell RNA-Seq Analyses for Studies of Spermatogonia

Robust methods have been developed that leverage next-generation sequencing (NGS) to measure abundance of all mRNAs (RNA-seq) in samples as small as individual cells in order to study the testicular transcriptome in mammals. In this chapter, we present robust options for implementing bioinformatics workflows for the analysis of bulk RNA-seq from aggregate samples of hundreds to millions of cells and single-cell RNA-seq from individual cells. We also provide detailed protocols for using the R packages DESeq2 and Seurat, important parameters for successful implementation, and considerations for drawing conclusions from the results.

Quality Control in Metagenomics Data

Experiments involving metagenomics data are become increasingly commonplace. Processing such data requires a unique set of considerations. Quality control of metagenomics data is critical to extracting pertinent insights. In this chapter, we outline some considerations in terms of study design and other confounding factors that can often only be realized at the point of data analysis.In this chapter, we outline some basic principles of quality control in metagenomics, including overall reproducibility and some good practices to follow. The general quality control of sequencing data is then outlined, and we introduce ways to process this data by using bash scripts and developing pipelines in Snakemake (Python).A significant part of quality control in metagenomics is in analyzing the data to ensure you can spot relationships between variables and to identify when they might be confounded. This chapter provides a walkthrough of analyzing some microbiome data (in the R statistical language) and demonstrates a few days to identify overall differences and similarities in microbiome data. The chapter is concluded by discussing remarks about considering taxonomic results in the context of the study and interrogating sequence alignments using the command line.

A Transcriptomic Analysis of Higher-Order Ecological Interactions in a Eukaryotic Model Microbial Ecosystem

Nonlinear ecological interactions within microbial ecosystems and their contribution to ecosystem functioning remain largely unexplored. Higher-order interactions, or interactions in systems comprised of more than two members that cannot be explained by cumulative pairwise interactions, are particularly understudied, especially in eukaryotic microorganisms. The wine fermentation ecosystem presents an ideal model to study yeast ecosystem establishment and functioning. Some pairwise ecological interactions between wine yeast species have been characterized, but very little is known about how more complex, multispecies systems function. Here, we evaluated nonlinear ecosystem properties by determining the transcriptomic response of Saccharomyces cerevisiae to pairwise versus tri-species culture. The transcriptome revealed that genes expressed during pairwise coculture were enriched in the tri-species data set but also that just under half of the data set comprised unique genes attributed to a higher-order response. Through interactive protein-association network visualizations, a holistic cell-wide view of the gene expression data was generated, which highlighted known stress response and metabolic adaptation mechanisms which were specifically activated during tri-species growth. Further, extracellular metabolite data corroborated that the observed differences were a result of a biotic stress response. This provides exciting new evidence showing the presence of higher-order interactions within a model microbial ecosystem. IMPORTANCE Higher-order interactions are one of the major blind spots in our understanding of microbial ecosystems. These systems remain largely unpredictable and are characterized by nonlinear dynamics, in particular when the system is comprised of more than two entities. By evaluating the transcriptomic response of S. cerevisiae to an increase in culture complexity from a single species to two- and three-species systems, we were able to confirm the presence of a unique response in the more complex setting that could not be explained by the responses observed at the pairwise level. This is the first data set that provides molecular targets for further analysis to explain unpredictable ecosystem dynamics in yeast.

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

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

Comprehensive drug response profiling and pan-omic analysis identified therapeutic candidates and prognostic biomarkers for Asian cholangiocarcinoma

Cholangiocarcinoma (CCA) is rare cancer with the highest incidence in Eastern and Southeast Asian countries. Advanced CCA patients rely on chemotherapeutic regimens that offer unsatisfied clinical outcomes. We developed a comprehensive drug response profiling to investigate potential new drugs using CCA cell lines from Thai and Japanese patients against 100 approved anti-cancer drugs. We identified two major CCA subgroups that displayed unique molecular pathways from our integrative pan-omic and ligand-induced pathway activation analyses. MEK and Src inhibitors specifically killed the CCA1 subgroup without causing cytotoxicity to the normal cholangiocyte. Next, we developed the CCA45 signature to classify CCA patients based on their transcriptomic data. Our CCA45 signature could accurately predict prognosis, especially for Asian CCA patients. Our study provides a comprehensive public resource for drug repurposing in CCA and introduces analytical strategies for prioritizing cancer therapeutic agents for other rare cancer.

Blood mRNA Expression in Alzheimer's Disease and Dementia With Lewy Bodies

OBJECTIVES

The objective of this study was to investigate the expression of genes in Alzheimer's disease (AD) and dementia with Lewy bodies (DLB), both at the mild cognitive impairment (MCI) and dementia stages, to improve our understanding of disease pathophysiology and investigate the potential for diagnostic and prognostic biomarkers based on mRNA expression.

DESIGN

Cross-sectional observational study.

SETTING

University research center.

PARTICIPANTS

People with MCI with Lewy bodies (MCI-LB, n=55), MCI-AD (n=19), DLB (n=38), AD (n=24) and a cognitively unimpaired comparison group (n=28).

MEASUREMENTS

Ribonucleic acid sequencing of whole blood. Differentially expressed genes (DEGs) were identified and gene set enrichment analysis was carried out.

RESULTS

Compared with the cognitively unimpaired group, there were 22 DEGs in MCI-LB/DLB and 61 DEGs in MCI-AD/AD. DEGS were also identified when comparing the two disease groups. Expression of ANP32A was associated with more rapid cognitive decline in MCI-AD/AD. Gene set enrichment analysis identified downregulation in gene sets including MYC targets and oxidative phosphorylation in MCI-LB/DLB; upregulation of immune and inflammatory responses in MCI-AD/AD; and upregulation of interferon-α and -γ responses in MCI-AD/AD compared with MCI-LB/DLB.

CONCLUSION

This study identified multiple DEGs in MCI-LB/DLB and MCI-AD/AD. One of these DEGs, ANP32A, may be a prognostic marker in AD. Genes related to mitochondrial function were downregulated in MCI-LB/DLB. Previously reported upregulation of genes associated with inflammation and immune responses in MCI-AD/AD was confirmed in this cohort. Differences in interferon responses between MCI-AD/AD and MCI-LB/DLB suggest that there are key differences in peripheral immune responses between these diseases.

Integrated COVID-19 Predictor: Differential expression analysis to reveal potential biomarkers and prediction of coronavirus using RNA-Seq profile data

Background

The world has been battling the continuous COVID-19 pandemic spread by the SARS-CoV-2 virus for last two years. The issue of viral disease prediction is constantly a matter of interest in virology and the study of disease transmission over the long years.

Objective

In this study, we aimed to implement genome association studies using RNA-Seq of COVID-19 and reveal highly expressed gene biomarkers and prediction based on the machine learning model of COVID-19 analysis to combat this pandemic.

Method

We collected RNA-Seq gene count data for both healthy (Control) and non-healthy (Treated) COVID-19 cases. In this experiment, a sequence of bioinformatics strategies and statistical techniques, such as fold-change and adjusted p-value, were processed to identify differentially expressed genes (DEGs). We filtered biomarker sets of high DEGs, moderate DEGs, and low DEGs using DESeq2, Limma Trend, and Limma Voom methods based on intersection and union operations and applied machine learning techniques to predict COVID-19.

Result

Through experimental analysis, 67 potential biomarkers were extracted, comprising 49 up-regulated and 18 down-regulated genes, using statistical techniques and a set-theory consensus strategy. We trained the machine learning models on 12 different biomarker sets and found that the SVM model performed better than the other classifiers with 99.07% classification accuracy for moderate DEGs.

Conclusion

Our study revealed that identified differentially expressed genes of the moderate DEGs biomarker set, |log2FC| ≥ 2 with adjusted p-value < 0.05, work significantly as input features to implement a machine learning model using a kernel-based SVM technique to predict COVID-19.

Leveraging big data bioinformatics approaches to extract knowledge from Staphylococcus aureus public omics data

Staphylococcus aureus is a notorious pathogen posing challenges in the medical industry due to drug resistance and biofilm formation. The horizon of knowledge on S. aureus pathogenesis has expanded with the advancement of data-driven bioinformatics techniques. Mining information from sequenced genomes and their expression data is an economic approach that alleviates wastage of resources and redundancy in experiments. The current review covers how big data bioinformatics has been used in the analysis of S. aureus from publicly available -omics data to uncover mechanisms of infection and inhibition. Particularly, advances in the past two decades in biomarker discovery, host responses, phenotype identification, consolidation of information, and drug development are discussed highlighting the challenges and shortcomings. Overall, the review summarizes the diverse aspects of scrupulous re-analysis of S. aureus proteomic and transcriptomic expression datasets retrieved from public repositories in terms of the efforts taken, benefits offered, and follow-up actions. The detailed review thus serves as a reference and aid for (i) Computational biologists by briefing the approaches utilized for bacterial omics re-analysis concerning S. aureus and (ii) Experimental biologists by elucidating the potential of bioinformatics in biological research to generate reliable postulates in a prompt and economical manner.

Transcriptomic dataset for early inflorescence stages of oil palm in response to defoliation stress

Oil palm breeding and seed development have been hindered due to the male parent's incapacity to produce male inflorescence as a source of pollen under normal conditions. On the other hand, a young oil palm plantation has a low pollination rate due to a lack of male flowers. These are the common problem of sex ratio in the oil palm industry. Nevertheless, the regulation of sex ratio in oil palm plants is a complex mechanism and remains an open question until now. Researchers have previously used complete defoliation to induce male inflorescences, but the biological and molecular mechanisms underlying this morphological change have yet to be discovered. Here, we present an RNA-seq dataset from three early stages of an oil palm inflorescence under normal conditions and complete defoliation stress. This transcriptomic dataset is a valuable resource to improve our understanding of sex determination mechanisms in oil palm inflorescence.

Characterization and Demonstration of Mock Communities as Control Reagents for Accurate Human Microbiome Community Measurements

Standardization and quality assurance of microbiome community analysis by high-throughput DNA sequencing require widely accessible and well-characterized reference materials. Here, we report on newly developed DNA and whole-cell mock communities to serve as control reagents for human gut microbiota measurements by shotgun metagenomics and 16S rRNA gene amplicon sequencing. The mock communities were formulated as near-even blends of up to 20 bacterial species prevalent in the human gut, span a wide range of genomic guanine-cytosine (GC) contents, and include multiple strains with Gram-positive type cell walls. Through a collaborative study, we carefully characterized the mock communities by shotgun metagenomics, using previously developed standardized protocols for DNA extraction and sequencing library construction. Further, we validated fitness of the mock communities for revealing technically meaningful differences among protocols for DNA extraction and metagenome/16S rRNA gene amplicon library construction. Finally, we used the mock communities to reveal varying performance of metagenome-based taxonomic profilers and the impact of trimming and filtering of sequencing reads on observed species profiles. The latter showed that aggressive preprocessing of reads may result in substantial GC-dependent bias and should thus be carefully evaluated to minimize unintended effects on species abundances. Taken together, the mock communities are expected to support a myriad of applications that rely on well-characterized control reagents, ranging from evaluation and optimization of methods to assessment of reproducibility in interlaboratory studies and routine quality control.

IMPORTANCE Application of high-throughput DNA sequencing has greatly accelerated human microbiome research and its translation into new therapeutic and diagnostic capabilities. Microbiome community analyses results can, however, vary considerably across studies or laboratories, and establishment of measurement standards to improve accuracy and reproducibility has become a priority. The here-developed mock communities, which are available from the NITE Biological Resource Center (NBRC) at the National Institute of Technology and Evaluation (NITE, Japan), provide well-characterized control reagents that allow users to judge the accuracy of their measurement results. Widespread and consistent adoption of the mock communities will improve reproducibility and comparability of microbiome community analyses, thereby supporting and accelerating human microbiome research and development.

Integrated multiple transcriptomes in oviductal tissue across the porcine estrous cycle reveal functional roles in oocyte maturation and transport

Understanding the changes in the swine female reproductive system is important for solving issues related to reproductive failure and litter size. Elucidating the regulatory mechanisms of the natural estrous cycle in the oviduct under non-fertilisation conditions can improve our understanding of its role in the reproductive system. Herein, whole transcriptome RNA sequencing of oviduct tissue samples was performed. The differentially expressed genes (DEGs) were identified for each time point relative to day 0 and classified into three clusters based on their expression patterns. Clusters 1 and 2 included genes involved in the physiological changes through the estrous cycle. Cluster 1 genes were mainly involved in PI3K-Akt signaling and steroid hormone biosynthesis pathways. Cluster 2 genes were involved in extracellular matrix-receptor interactions and protein digestion pathways. In Cluster 3, the DEGs were downregulated in the luteal phase; they were strongly associated with cell cycle, calcium signaling, and oocyte meiosis. The gene expression in the oviduct during the estrous cycle influenced oocyte transport and fertilization. Our findings provide a basis for successfully breeding pigs and elucidating the mechanisms underlying the changes in the pig oviduct during the estrous cycle.

Regulation of fatty acid desaturase- and immunity gene-expression by mbk-1/DYRK1A in Caenorhabditis elegans

BACKGROUND

In the nematode Caenorhabditis elegans, longevity in response to germline ablation, but not in response to reduced insulin/IGF1-like signaling, is strongly dependent on the conserved protein kinase minibrain-related kinase 1 (MBK-1). In humans, the MBK-1 ortholog DYRK1A is associated with a variety of disorders, most prominently with neurological defects observed in Down syndrome. To better understand mbk-1's physiological roles and their dependence on genetic background, we analyzed the influence of mbk-1 loss on the transcriptomes of wildtype and long-lived, germline-deficient or insulin-receptor defective, C. elegans strains by RNA-sequencing.

RESULTS

mbk-1 loss elicited global changes in transcription that were less pronounced in insulin-receptor mutant than in germline-deficient or wildtype C. elegans. Irrespective of genetic background, mbk-1 regulated genes were enriched for functions in biological processes related to organic acid metabolism and pathogen defense. qPCR-studies confirmed mbk-1 dependent induction of all three C. elegans Δ9-fatty acid desaturases, fat-5, fat-6 and fat-7, in wildtype, germline-deficient and insulin-receptor mutant strains. Conversely, mbk-1 dependent expression patterns of selected pathogen resistance genes, including asp-12, dod-24 and drd-50, differed across the genetic backgrounds examined. Finally, cth-1 and cysl-2, two genes which connect pathogen resistance to the metabolism of the gaseous messenger and lifespan regulator hydrogen sulfide (H₂S), were commonly suppressed by mbk-1 loss only in wildtype and germline-deficient, but not in insulin-receptor mutant C. elegans.

CONCLUSION

Our work reveals previously unknown roles of C. elegans mbk-1 in the regulation of fatty acid desaturase- and H₂S metabolic-genes. These roles are only partially dependent on genetic background. Considering the particular importance of fatty acid desaturation and H₂S for longevity of germline-deficient C. elegans, we propose that these processes at least in part account for the previous observation that mbk-1 preferentially regulates lifespan in these worms.

Analysis of ROS-Triggered Changes in the Transcriptome

RNA sequencing is routinely used for determining transcriptome-wide expression changes during various conditions, including oxidative stress conditions. In this chapter, a basic workflow to determine differentially expressed genes between two conditions of interest is provided. After providing brief guidelines for experimental design, we provide step-by-step instructions for genome alignment of reads and differential expression analysis.

Integrated de novo Analysis of Transcriptional and Metabolic Variations in Salt-Treated Solenostemma argel Desert Plants

Solenostemma argel (Delile) Hayne is a desert plant that survives harsh environmental conditions with several vital medicinal properties. Salt stress is a major constraint limiting agricultural production around the globe. However, response mechanisms behind the adaptation of S. argel plants to salt stress are still poorly understood. In the current study, we applied an omics approach to explore how this plant adapts to salt stress by integrating transcriptomic and metabolomic changes in the roots and leaves of S. argel plants under salt stress. De novo assembly of transcriptome produced 57,796 unigenes represented by 165,147 transcripts/isoforms. A total of 730 differentially expressed genes (DEGs) were identified in the roots (396 and 334 were up- and down-regulated, respectively). In the leaves, 927 DEGs were identified (601 and 326 were up- and down-regulated, respectively). Gene ontology and Kyoto Encyclopedia of Genes And Genomes pathway enrichment analyses revealed that several defense-related biological processes, such as response to osmotic and oxidative stress, hormonal signal transduction, mitogen-activated protein kinase signaling, and phenylpropanoid biosynthesis pathways are the potential mechanisms involved in the tolerance of S. argel plants to salt stress. Furthermore, liquid chromatography-tandem mass spectrometry was used to detect the metabolic variations of the leaves and roots of S. argel under control and salt stress. 45 and 56 critical metabolites showed changes in their levels in the stressed roots and leaves, respectively; there were 20 metabolites in common between the roots and leaves. Differentially accumulated metabolites included amino acids, polyamines, hydroxycinnamic acids, monolignols, flavonoids, and saccharides that improve antioxidant ability and osmotic adjustment of S. argel plants under salt stress. The results present insights into potential salt response mechanisms in S. argel desert plants and increase the knowledge in order to generate more tolerant crops to salt stress.

Somatostatin and Its Receptors in Myocardial Ischemia/Reperfusion Injury and Cardioprotection

Little is known about the role of the neuropeptide somatostatin (SST) in myocardial ischemia/reperfusion injury and cardioprotection. Here, we investigated the direct cardiocytoprotective effect of SST on ischemia/reperfusion injury in cardiomyocyte cultures, as well as the expression of SST and its receptors in pig and human heart tissues. SST induced a bell-shaped, concentration-dependent cardiocytoprotection in both adult rat primary cardiomyocytes and H9C2 cells subjected to simulated ischemia/reperfusion injury. Furthermore, in a translational porcine closed-chest acute myocardial infarction model, ischemic preconditioning increased plasma SST-like immunoreactivity. Interestingly, SST expression was detectable at the protein, but not at the mRNA level in the pig left ventricles. SSTR1 and SSTR2, but not the other SST receptors, were detectable at the mRNA level by PCR and sequencing in the pig left ventricle. Moreover, remote ischemic conditioning upregulated SSTR1 mRNA. Similarly, SST expression was also detectable in healthy human interventricular septum samples at the protein level. Furthermore, SST-like immunoreactivity decreased in interventricular septum samples of patients with ischemic cardiomyopathy. SSTR1, SSTR2, and SSTR5 but not SST and the other SST receptors were detectable at the mRNA level by sequencing in healthy human left ventricles. In addition, in healthy human left ventricle samples, SSTR1 and SSTR2 mRNAs were expressed especially in vascular endothelial and some other cell types as detected by RNA Scope® in situ hybridization. This is the first demonstration that SST exerts a direct cardiocytoprotective effect against simulated ischemia/reperfusion injury. Moreover, SST is expressed in the heart tissue at the peptide level; however, it is likely to be of sensory neural origin since its mRNA is not detectable. SSTR1 and SSTR2 might be involved in the cardioprotective action of SST, but other mechanisms cannot be excluded.

Two Interferon-Stimulated Response Elements Cooperatively Regulate Interferon-Stimulated Gene Expression in West Nile Virus-Infected IFNAR-/- Mouse Embryo Fibroblasts

We previously identified a subset of interferon-stimulated genes (ISGs) upregulated by West Nile virus (WNV) infection in wild-type mouse embryo fibroblasts (MEFs) after viral proteins had inhibited type I interferon (IFN)-mediated JAK-STAT signaling and also in WNV-infected RIG-I^-/-, MDA5^-/-, STAT1^-/-, STAT2^-/-, IFNAR^-/-, IRF3^-/-, IRF7^-/-, and IRF3/7^-/- MEFs. In this study, ISG upregulation by WNV infection in IFNAR^-/- MEFs was confirmed by transcriptome sequencing (RNA-seq). ISG upregulation by WNV infection was inhibited in RIG-I/MDA5^-/- MEFs. ISGs were upregulated in IRF1^-/- and IRF5^-/- MEFs but only minimally upregulated in IRF3/5/7^-/- MEFs, suggesting redundant IRF involvement. We previously showed that a single proximal interferon-stimulated response element (ISRE) in the Oas1a and Oas1b promoters bound the ISGF3 complex after type I IFN treatment. In this study, we used wild-type and mutant promoter luciferase reporter constructs to identify critical regions in the Oas1b and Ifit1 promoters for gene activation in infected IFNAR^-/- MEFs. Two ISREs were required in both promoters. Mutation of these ISREs in an Ifit1 promoter DNA probe reduced in vitro complex formation with infected nuclear extracts. An NF-κB inhibitor decreased Ifit1 promoter activity in cells and in vitro complex formation. IRF3 and p50 promoter binding was detected by chromatin immunoprecipitation (ChIP) for upregulated ISGs with two proximal ISREs. The data indicate that ISREs function cooperatively to upregulate the expression of some ISGs when type I IFN signaling is absent, with the binding complex consisting of IRF3, IRF5, and/or IRF7 and an NF-κB component(s) as well as other, as-yet-unknown factors. IMPORTANCE Type I IFN signaling in mammalian cells induces formation of the ISGF3 transcription factor complex, which binds to interferon stimulated response elements (ISREs) in the promoters of interferon-stimulated genes (ISGs) in the cell nucleus. Flavivirus proteins counteract type I IFN signaling by preventing either the formation or nuclear localization of ISGF3. A subset of ISRE-regulated ISGs was still induced in West Nile virus (WNV)-infected mouse embryo fibroblasts (MEFs), indicating that cells have an alternative mechanism for activating these ISGs. In this study, cellular components involved in this ISG upregulation mechanism were identified using gene knockout MEFs and ChIP, and critical promoter regions for gene activation were mapped using reporter assays. The data indicate a cooperative function between two ISREs and required binding of IRF3, IRF5, and/or IRF7 and an NF-κB component(s). Moreover, type I IFN signaling-independent ISG activation requires different additional promoter activation regions than type I IFN-dependent activation.

Spatial variation in gene expression of Tasmanian devil facial tumors despite minimal host transcriptomic response to infection

BACKGROUND

Transmissible cancers lie at the intersection of oncology and infectious disease, two traditionally divergent fields for which gene expression studies are particularly useful for identifying the molecular basis of phenotypic variation. In oncology, transcriptomics studies, which characterize the expression of thousands of genes, have identified processes leading to heterogeneity in cancer phenotypes and individual prognoses. More generally, transcriptomics studies of infectious diseases characterize interactions between host, pathogen, and environment to better predict population-level outcomes. Tasmanian devils have been impacted dramatically by a transmissible cancer (devil facial tumor disease; DFTD) that has led to widespread population declines. Despite initial predictions of extinction, populations have persisted at low levels, due in part to heterogeneity in host responses, particularly between sexes. However, the processes underlying this variation remain unknown.

RESULTS

We sequenced transcriptomes from healthy and DFTD-infected devils, as well as DFTD tumors, to characterize host responses to DFTD infection, identify differing host-tumor molecular interactions between sexes, and investigate the extent to which tumor gene expression varies among host populations. We found minimal variation in gene expression of devil lip tissues, either with respect to DFTD infection status or sex. However, 4088 genes were differentially expressed in tumors among our sampling localities. Pathways that were up- or downregulated in DFTD tumors relative to normal tissues exhibited the same patterns of expression with greater intensity in tumors from localities that experienced DFTD for longer. No mRNA sequence variants were associated with expression variation.

CONCLUSIONS

Expression variation among localities may reflect morphological differences in tumors that alter ratios of normal-to-tumor cells within biopsies. Phenotypic variation in tumors may arise from environmental variation or differences in host immune response that were undetectable in lip biopsies, potentially reflecting variation in host-tumor coevolutionary relationships among sites that differ in the time since DFTD arrival.

Temperature-dependent effects of house fly proto-Y chromosomes on gene expression could be responsible for fitness differences that maintain polygenic sex determination

Sex determination, the developmental process by which sexually dimorphic phenotypes are established, evolves fast. Evolutionary turnover in a sex determination pathway may occur via selection on alleles that are genetically linked to a new master sex determining locus on a newly formed proto-sex chromosome. Species with polygenic sex determination, in which master regulatory genes are found on multiple different proto-sex chromosomes, are informative models to study the evolution of sex determination and sex chromosomes. House flies are such a model system, with male determining loci possible on all six chromosomes and a female-determiner on one of the chromosomes as well. The two most common male-determining proto-Y chromosomes form latitudinal clines on multiple continents, suggesting that temperature variation is an important selection pressure responsible for maintaining polygenic sex determination in this species. Temperature-dependent fitness effects could be manifested through temperature-dependent gene expression differences across proto-Y chromosome genotypes. These gene expression differences may be the result of cis regulatory variants that affect the expression of genes on the proto-sex chromosomes, or trans effects of the proto-Y chromosomes on genes elswhere in the genome. We used RNA-seq to identify genes whose expression depends on proto-Y chromosome genotype and temperature in adult male house flies. We found no evidence for ecologically meaningful temperature-dependent expression differences of sex determining genes between male genotypes, but we were probably not sampling an appropriate developmental time-point to identify such effects. In contrast, we identified many other genes whose expression depends on the interaction between proto-Y chromosome genotype and temperature, including genes that encode proteins involved in reproduction, metabolism, lifespan, stress response, and immunity. Notably, genes with genotype-by-temperature interactions on expression were not enriched on the proto-sex chromosomes. Moreover, there was no evidence that temperature-dependent expression is driven by chromosome-wide cis-regulatory divergence between the proto-Y and proto-X alleles. Therefore, if temperature-dependent gene expression is responsible for differences in phenotypes and fitness of proto-Y genotypes across house fly populations, these effects are driven by a small number of temperature-dependent alleles on the proto-Y chromosomes that may have trans effects on the expression of genes on other chromosomes.

JWES: a new pipeline for whole genome/exome sequence data processing, management, and gene-variant discovery, annotation, prediction, and genotyping

Whole genome and exome sequencing (WGS/WES) are the most popular next‐generation sequencing (NGS) methodologies and are at present often used to detect rare and common genetic variants of clinical significance. We emphasize that automated sequence data processing, management, and visualization should be an indispensable component of modern WGS and WES data analysis for sequence assembly, variant detection (SNPs, SVs), imputation, and resolution of haplotypes. In this manuscript, we present a newly developed findable, accessible, interoperable, and reusable (FAIR) bioinformatics‐genomics pipeline Java based Whole Genome/Exome Sequence Data Processing Pipeline (JWES) for efficient variant discovery and interpretation, and big data modeling and visualization. JWES is a cross‐platform, user‐friendly, product line application, that entails three modules: (a) data processing, (b) storage, and (c) visualization. The data processing module performs a series of different tasks for variant calling, the data storage module efficiently manages high‐volume gene‐variant data, and the data visualization module supports variant data interpretation with Circos graphs. The performance of JWES was tested and validated in‐house with different experiments, using Microsoft Windows, macOS Big Sur, and UNIX operating systems. JWES is an open‐source and freely available pipeline, allowing scientists to take full advantage of all the computing resources available, without requiring much computer science knowledge. We have successfully applied JWES for processing, management, and gene‐variant discovery, annotation, prediction, and genotyping of WGS and WES data to analyze variable complex disorders. In summary, we report the performance of JWES with some reproducible case studies, using open access and in‐house generated, high‐quality datasets.

Non-coding Natural Antisense Transcripts: Analysis and Application

Non-coding natural antisense transcripts (ncNATs) are regulatory RNA sequences that are transcribed in the opposite direction to protein-coding or non-coding transcripts. These transcripts are implicated in a broad variety of biological and pathological processes, including tumorigenesis and oncogenic progression. With this complex field still in its infancy, annotations, expression profiling and functional characterisations of ncNATs are far less comprehensive than those for protein-coding genes, pointing out substantial gaps in the analysis and characterisation of these regulatory transcripts. In this review, we discuss ncNATs from an analysis perspective, in particular regarding the use of high-throughput sequencing strategies, such as RNA-sequencing, and summarize the unique challenges of investigating the antisense transcriptome. Finally, we elaborate on their potential as biomarkers and future targets for treatment, focusing on cancer.

NASA GeneLab RNA-seq consensus pipeline: standardized processing of short-read RNA-seq data

With the development of transcriptomic technologies, we are able to quantify precise changes in gene expression profiles from astronauts and other organisms exposed to spaceflight. Members of NASA GeneLab and GeneLab-associated analysis working groups (AWGs) have developed a consensus pipeline for analyzing short-read RNA-sequencing data from spaceflight-associated experiments. The pipeline includes quality control, read trimming, mapping, and gene quantification steps, culminating in the detection of differentially expressed genes. This data analysis pipeline and the results of its execution using data submitted to GeneLab are now all publicly available through the GeneLab database. We present here the full details and rationale for the construction of this pipeline in order to promote transparency, reproducibility, and reusability of pipeline data; to provide a template for data processing of future spaceflight-relevant datasets; and to encourage cross-analysis of data from other databases with the data available in GeneLab.

Probing into the Effects of Grapevine Leafroll-Associated Viruses on the Physiology, Fruit Quality and Gene Expression of Grapes

Grapevine leafroll is one of the most widespread and highly destructive grapevine diseases that is responsible for great economic losses to the grape and wine industries throughout the world. Six distinct viruses have been implicated in this disease complex. They belong to three genera, all in the family Closteroviridae. For the sake of convenience, these viruses are named as grapevine leafroll-associated viruses (GLRaV-1, -2, -3, -4, -7, and -13). However, their etiological role in the disease has yet to be established. Furthermore, how infections with each GLRaV induce the characteristic disease symptoms remains unresolved. Here, we first provide a brief overview on each of these GLRaVs with a focus on genome structure, expression strategies and gene functions, where available. We then provide a review on the effects of GLRaV infection on the physiology, fruit quality, fruit chemical composition, and gene expression of grapevine based on the limited information so far reported in the literature. We outline key methodologies that have been used to study how GLRaV infections alter gene expression in the grapevine host at the transcriptomic level. Finally, we present a working model as an initial attempt to explain how infections with GLRaVs lead to the characteristic symptoms of grapevine leafroll disease: leaf discoloration and downward rolling. It is our hope that this review will serve as a starting point for grapevine virology and the related research community to tackle this vastly important and yet virtually uncharted territory in virus-host interactions involving woody and perennial fruit crops.