Estimating accuracy of RNA-Seq and microarrays with proteomics

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

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

Whole blood transcriptomics identifies subclasses of pediatric septic shock

BACKGROUND

Sepsis is a highly heterogeneous syndrome, which has hindered the development of effective therapies. This has prompted investigators to develop a precision medicine approach aimed at identifying biologically homogenous subgroups of patients with septic shock and critical illnesses. Transcriptomic analysis can identify subclasses derived from differences in underlying pathophysiological processes that may provide the basis for new targeted therapies. The goal of this study was to elucidate pathophysiological pathways and identify pediatric septic shock subclasses based on whole blood RNA expression profiles.

METHODS

The subjects were critically ill children with cardiopulmonary failure who were a part of a prospective randomized insulin titration trial to treat hyperglycemia. Genome-wide expression profiling was conducted using RNA sequencing from whole blood samples obtained from 46 children with septic shock and 52 mechanically ventilated noninfected controls without shock. Patients with septic shock were allocated to subclasses based on hierarchical clustering of gene expression profiles, and we then compared clinical characteristics, plasma inflammatory markers, cell compositions using GEDIT, and immune repertoires using Imrep between the two subclasses.

RESULTS

Patients with septic shock depicted alterations in innate and adaptive immune pathways. Among patients with septic shock, we identified two subtypes based on gene expression patterns. Compared with Subclass 2, Subclass 1 was characterized by upregulation of innate immunity pathways and downregulation of adaptive immunity pathways. Subclass 1 had significantly worse clinical outcomes despite the two classes having similar illness severity on initial clinical presentation. Subclass 1 had elevated levels of plasma inflammatory cytokines and endothelial injury biomarkers and demonstrated decreased percentages of CD4 T cells and B cells and less diverse T cell receptor repertoires.

CONCLUSIONS

Two subclasses of pediatric septic shock patients were discovered through genome-wide expression profiling based on whole blood RNA sequencing with major biological and clinical differences. Trial Registration This is a secondary analysis of data generated as part of the observational CAF-PINT ancillary of the HALF-PINT study (NCT01565941). Registered March 29, 2012.

Whole Blood Transcriptomics Identifies Subclasses of Pediatric Septic Shock

Background

Sepsis is a highly heterogeneous syndrome, that has hindered the development of effective therapies. This has prompted investigators to develop a precision medicine approach aimed at identifying biologically homogenous subgroups of patients with septic shock and critical illnesses. Transcriptomic analysis can identify subclasses derived from differences in underlying pathophysiological processes that may provide the basis for new targeted therapies. The goal of this study was to elucidate pathophysiological pathways and identify pediatric septic shock subclasses based on whole blood RNA expression profiles.

Methods

The subjects were critically ill children with cardiopulmonary failure who were a part of a prospective randomized insulin titration trial to treat hyperglycemia. Genome-wide expression profiling was conducted using RNA-sequencing from whole blood samples obtained from 46 children with septic shock and 52 mechanically ventilated noninfected controls without shock. Patients with septic shock were allocated to subclasses based on hierarchical clustering of gene expression profiles, and we then compared clinical characteristics, plasma inflammatory markers, cell compositions using GEDIT, and immune repertoires using Imrep between the two subclasses.

Results

Patients with septic shock depicted alterations in innate and adaptive immune pathways. Among patients with septic shock, we identified two subtypes based on gene expression patterns. Compared with Subclass 2, Subclass 1 was characterized by upregulation of innate immunity pathways and downregulation of adaptive immunity pathways. Subclass 1 had significantly worse clinical outcomes despite the two classes having similar illness severity on initial clinical presentation. Subclass 1 had elevated levels of plasma inflammatory cytokines and endothelial injury biomarkers and demonstrated decreased percentages of CD4 T cells and B cells, and less diverse T-Cell receptor repertoires.

Conclusions

Two subclasses of pediatric septic shock patients were discovered through genome-wide expression profiling based on whole blood RNA sequencing with major biological and clinical differences.

Trial Registration

This is a secondary analysis of data generated as part of the observational CAF PINT ancillary of the HALF PINT study (NCT01565941). Registered 29 March 2012.

Peonidin-3-O-glucoside and Resveratrol Increase the Viability of Cultured Human hFOB Osteoblasts and Alter the Expression of Genes Associated with Apoptosis, Osteoblast Differentiation and Osteoclastogenesis

High-throughput RNA-sequencing can determine the impact of nutrients and their combinations on gene transcription levels in osteocytes, and clarify the biological pathways associated with their impact on bone tissues. Previously, we reported that resveratrol (RES) and peonidin-3-O-glucoside (POG) increased osteoblastogenesis, as well as reduced osteoclastogenesis in transgenic teleost fish models. Here, we perform whole-genome transcriptomic profiling of osteoblasts treated with POG or RES to provide a comprehensive understanding of alterations in gene expression and the molecular mechanisms involved. Cultured human fetal osteoblastic hFOB 1.19 cells were treated with the test compounds, and then RNA was used to prepare RNA-seq libraries, that were sequenced using a NovaSeq 6000. Treatment with POG or RES increased osteoblast proliferation and reduced apoptosis. Transcriptomic profiling showed that of the 29,762 genes investigated, 3177 were differentially expressed (1481 upregulated, 1696 downregulated, FDR ≤ 0.05) in POG-treated osteoblasts. In the RES-treated osteoblasts, 2288 genes were differentially expressed (DGEs, 1068 upregulated, 1220 downregulated, FDR ≤ 0.05). Ingenuity^® Pathway Analysis (IPA) of DGEs from RES or POG-treated osteoblasts revealed significant downregulation of the apoptosis, osteoarthritis and HIF1α canonical pathways, and a significant reduction in Rankl mRNA expression. The data suggest that RES and POG have both anabolic and anticlastogenic effects.

Differentially expressed genes in systemic sclerosis: Towards predictive medicine with new molecular tools for clinicians

Systemic sclerosis (SSc) is a rare and chronic autoimmune disease characterized by a pathogenic triad of immune dysregulation, vasculopathy, and progressive fibrosis. Clinical tools commonly used to assess patients, such as the modified Rodnan skin score, difference between limited or diffuse forms of skin involvement, presence of lung, heart or kidney involvement, or of various autoantibodies, are important prognostic factors, but still fail to reflect the large heterogeneity of the disease. SSc treatment options are diverse, ranging from conventional drugs to autologous hematopoietic stem cell transplantation, and predicting response is challenging. Genome-wide technologies, such as high throughput microarray analyses and RNA sequencing, allow accurate, unbiased, and broad assessment of alterations in expression levels of multiple genes. In recent years, many studies have shown robust changes in the gene expression profiles of SSc patients compared to healthy controls, mainly in skin tissues and peripheral blood cells. The objective analysis of molecular patterns in SSc is a powerful tool that can further classify SSc patients with similar clinical phenotypes and help predict response to therapy. In this review, we describe the journey from the first discovery of differentially expressed genes to the identification of enriched pathways and intrinsic subsets identified in SSc, using machine learning algorithms. Finally, we discuss the use of these new tools to predict the efficacy of various treatments, including stem cell transplantation. We suggest that the use of RNA gene expression-based classifications according to molecular subsets may bring us one step closer to precision medicine in Systemic Sclerosis.

Transcriptome-Based Evaluation of Optimal Reference Genes for Quantitative Real-Time PCR in Yak Stomach throughout the Growth Cycle

Efficient nutritional assimilation and energy metabolism in the stomachs of yaks contribute to their adaption to harsh environments. Accurate gene expression profile analysis will help further reveal the molecular mechanism of nutrient and energy metabolism in the yak stomach. RT-qPCR is regarded as an accurate and dependable method for analyzing gene expression. The selection of reference genes is essential to obtain meaningful RT-qPCR results, especially in longitudinal gene expression studies of tissues and organs. Our objective was to select and validate optimal reference genes from across the transcriptome as internal controls for longitudinal gene expression studies in the yak stomach. In this study, 15 candidate reference genes (CRGs) were determined according to transcriptome sequencing (RNA-seq) results and the previous literature. The expression levels of these 15 CRGs were quantified using RT-qPCR in the yak stomach, including the rumen, reticulum, omasum and abomasum at five stages: 0 days, 20 days, 60 days, 15 months and three years old (adult). Subsequently, the expression stabilities of these 15 CRGs were evaluated via four algorithms: geNorm, NormFinder, BestKeeper and the comparative C_T method. Furthermore, RefFinder was employed to obtain a comprehensive ranking of the stability of CRGs. The analysis results indicate that RPS15, MRPL39 and RPS23 are the most stable genes in the yak stomach throughout the growth cycle. In addition, to verify the reliability of the selected CRGs, the relative expression levels of HMGCS2 were quantified via RT-qPCR using the three most stable or the three least stable CRGs. Overall, we recommend combining RPS15, MRPL39 and RPS23 as reference genes for the normalization of RT-qPCR data in the yak stomach throughout the growth cycle.

In utero exposure to methylmercury impairs cognitive function in adult offspring: Insights from proteomic modulation

Methylmercury (MeHg) is a hazardous substance that has unique neurodevelopmental toxic effects. However, its molecular alteration profile, sensitive response biomarkers, and mechanism of neuronal injury remain largely unknown. Here, the effects of intrauterine methylmercury chloride (low-, medium- and high-dose groups: 0.6 mg/kg/d, 1.2 mg/kg/d, 2.4 mg/ kg /d, respectively) exposure on learning and memory were assessed in offspring rats by behavioral tests, pathological analysis and hippocampal proteomic analysis. The results suggested that intrauterine MeHg exposure impairs spatial learning and memory and leads a significant reduction in the number and dispersion scattered arrangement in the hippocampus of offspring. Furthermore, in the tandem mass tag-based proteomics analysis, compared with the control group, a total of 74 differentially expressed proteins (DEPs) were found in the MeHg exposure groups; specifically, 32 down-regulated and 42 up-regulated proteins were identified. In addition, the pathways enrichment analysis indicated that these DEPs are implicated in several biological processes, such as synaptic plasticity and energy metabolism, as well as various molecular functional categories. Simultaneously, MeHg reduced the postsynaptic density, diminished the active zone, amplified the synaptic cleft and changed the synaptic interface of pyramidal cells. Western blot analysis further revealed that MeHg significantly reduced the levels of Forkhead box protein (FOXP2), Synaptophysin (SYP) and Postsynaptic density protein 95 (PSD-95), and down-regulated the N-methyl-D-aspartate receptor 1 (NMDAR1), N-methyl-D-aspartate receptor 2 A (NR2A) and N-methyl-D-aspartate receptor 2B (NR2B). In general, from a functional perspective, most overlapping proteins were related to NMDA receptor-mediated glutamatergic signaling, which is an excitotoxicity mechanism known to influence learning and memory. These discoveries contribute to our understanding of the relationship between MeHg and cognitive deficits and provide insight into the protein mediators of this relationship and possible prospective early biomarkers.

Gene Expression Profiling of FFPE Samples: A Titration Test

The gene expression analysis of formalin-fixed paraffin-embedded (FFPE) tissues is often hampered by poor RNA quality, which results from the oxidation, cross-linking and other chemical modifications induced by the inclusion in paraffin. Yet, FFPE samples are a valuable source for molecular studies and can provide great insights into disease progression and prognosis. With the advancement of genomic technologies, new methods have been established that offer reliable and accurate gene expression workflows on samples of poor quality. NanoString is a probe-based technology that allows the direct counting of the mRNA transcripts and can be applied to degraded samples. Here, we have tested 2 RNA extraction methods for FFPE samples, and we have performed a titration experiment to evaluate the impact of RNA degradation and RNA input on the gene expression profiles assessed using the NanoString IO360 panel. We have selected FFPE samples of different DV200 values and assessed them on the nCounter platform with 2 different amounts of input RNA. This study concludes that the nCounter is a robust and reliable platform to assess the gene expression of RNA samples with DV200 > 30%; its robustness and ease of use could be of particular benefit to clinical settings.

Identification of key genes for HNSCC from public databases using bioinformatics analysis

Background

The cause and underlying molecular mechanisms of head and neck squamous cell carcinoma (HNSCC) are unclear. Our study aims to identify the key genes associated with HNSCC and reveal potential biomarkers.

Methods

In this study, the expression profile dataset GSE83519 of the Gene Expression Omnibus database and the RNA sequencing dataset of HNSCC of The Cancer Genome Atlas were included for analysis. Sixteen differentially expressed genes were screened from these two datasets using R software. Gene Expression Profiling Interactive Analysis 2 (GEPIA2) was then adopted for survival analysis, and finally, three key genes related to the overall survival of HNSCC patients were identified. Furthermore, we verified these three genes using the Oncomine database and from real-time PCR and immunohistochemistry results from HNSCC tissues.

Results

The expression data of 44 samples from GSE83519 and 545 samples from TCGA-HNSC were collected. Using bioinformatics, the two databases were integrated, and 16 DEGs were screened out. Gene Ontology (GO) enrichment analysis showed that the biological functions of DEGs focused primarily on the apical plasma membrane and regulation of anoikis. Kyoto Encyclopedia of Genes and Genomes (KEGG) signalling pathway analysis showed that these DEGs were mainly involved in drug metabolism-cytochrome P450 and serotonergic synapses. Survival analysis identified three key genes, CEACAM5, CEACAM6 and CLCA4, that were closely related to HNSCC prognosis. The Oncomine database, qRT–PCR and IHC verified that all 3 key genes were downregulated in most HNSCC tissues compared to adjacent normal tissues.

Conclusions

This study indicates that integrated bioinformatics analyses play an important role in screening for differentially expressed genes and pathways in HNSCC, helping us better understand the biomarkers and molecular mechanism of HNSCC.

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

OBJECTIVE

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

BACKGROUND

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

METHODS

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

CONCLUSIONS

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

Loss of Gene Information: Discrepancies between RNA Sequencing, cDNA Microarray, and qRT-PCR

Molecular analyses of normal and diseased cells give insight into changes in gene expression and help in understanding the background of pathophysiological processes. Years after cDNA microarrays were established in research, RNA sequencing (RNA-seq) became a key method of quantitatively measuring the transcriptome. In this study, we compared the detection of genes by each of the transcriptome analysis methods: cDNA array, quantitative RT-PCR, and RNA-seq. As expected, we found differences in the gene expression profiles of the aforementioned techniques. Here, we present selected genes that exemplarily demonstrate the observed differences and calculations to reveal that a strong RNA secondary structure, as well as sample preparation, can affect RNA-seq. In summary, this study addresses an important issue with a strong impact on gene expression analysis in general. Therefore, we suggest that these findings need to be considered when dealing with data from transcriptome analyses.

Systematic Identification and Validation of Housekeeping and Tissue-Specific Genes in Allotetraploid Chenopodium quinoa

Quinoa is a gluten-free food crop that contains all the essential amino acids and vitamins. The selection of proper housekeeping and tissue-specific genes is the crucial prerequisite for gene expression analysis using the common approach, real-time quantitative PCR (RT-qPCR). In this study, we identified 40 novel candidate housekeeping genes by the minimum transcript per million (TPM), coefficient of variation (CV) and maximum fold change (MFC) methods and 19 candidate tissue-specific genes by the co-expression network method based on an RNA-seq dataset that included 53 stem, leaf, flower and seed samples, as well as additional shoot and root samples under different stresses. The expression stability of 12 housekeeping and tissue-specific genes, as well as that of another two traditionally used housekeeping genes, was further evaluated using qPCR and ranked using NormFinder, BestKeeper and the comparative delta-Ct method. The results demonstrated that MIF, RGGA, VATE and UBA2B were ranked as the top four most stable candidate housekeeping genes. qPCR analysis also revealed three leaf-specific genes and five root-specific genes, but no stem-specific gene was identified. Gene Ontology (GO) enrichment analysis identified that housekeeping genes were mainly enriched in the small molecule metabolic process, organonitrogen compound metabolic process, NAD binding and ligase activity. In addition, tissue-specific genes are closely associated with the major functions of a specific tissue. Specifically, GO terms “photosynthesis” and “thylakoid” were most significantly overrepresented in candidate leaf-specific genes. The novel housekeeping and tissue-specific genes in our study will enable better normalization and quantification of transcript levels in quinoa.

Quantitative proteomic analysis to capture the role of heat-accumulated proteins in moss plant acquired thermotolerance

At dawn of a scorching summer day, land plants must anticipate upcoming extreme midday temperatures by timely establishing molecular defences that can keep heat-labile membranes and proteins functional. A gradual morning pre-exposure to increasing sub-damaging temperatures induces heat-shock proteins (HSPs) that are central to the onset of plant acquired thermotolerance (AT). To gain knowledge on the mechanisms of AT in the model land plant Physcomitrium patens, we used label-free LC-MS/MS proteomics to quantify the accumulated and depleted proteins before and following a mild heat-priming treatment. High protein crowding is thought to promote protein aggregation, whereas molecular chaperones prevent and actively revert aggregation. Yet, we found that heat priming (HP) did not accumulate HSP chaperones in chloroplasts, although protein crowding was six times higher than in the cytosol. In contrast, several HSP20s strongly accumulated in the cytosol, yet contributing merely 4% of the net mass increase of heat-accumulated proteins. This is in poor concordance with their presumed role at preventing the aggregation of heat-labile proteins. The data suggests that under mild HP unlikely to affect protein stability. Accumulating HSP20s leading to AT, regulate the activity of rare and specific signalling proteins, thereby preventing cell death under noxious heat stress.

Sustained Stimulation of β2AR Inhibits Insulin Signaling in H9C2 Cardiomyoblast Cells Through the PKA-Dependent Signaling Pathway

INTRODUCTION

This study aimed to investigate the role of β2 adrenergic receptor (β2AR) in insulin signaling transduction in H9C2 cardiomyoblast cells to understand the formation of the β2AR-insulin receptor (IR) protein complex and its role in insulin-induced Glut4 expression.

METHODS

H9C2 cells were treated with various protein inhibitors (CGP, β1AR inhibitor CGP20712; ICI, β2AR inhibitor ICI 118,551; PKI, PKA inhibitor myristoylated PKI; PD 0325901, MEK inhibitor; SP600125, JNK inhibitor) with or without insulin or isoproterenol (ISO) before RNA-sequencing (RNA-Seq) and quantitative-PCR (Q-PCR). Yeast two-hybrid, co-immunoprecipitation and His-tag pull-down assay were carried out to investigate the formation of the β2AR-IR protein complex. The intracellular concentrations of cAMP in H9C2 cells were tested by high performance liquid chromatography (HPLC) and the phosphorylation of JNK was tested by Western blot.

RESULTS

Gene Ontology (GO) analysis revealed that the most significantly enriched processes in the domain of molecular function (MF) were catalytic activity and binding, whereas in the domain of biological processes (BP) were metabolic process and cellular process. Furthermore, the enriched processes in the domain of cellular components (CC) were cell and cell parts. The Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis showed that the most significant pathways that have been altered included the PI3K-Akt and MAPK signaling pathways. Q-PCR, which was performed to verify the gene expression levels exhibited consistent results. In evaluating the signaling pathways, the sustained stimulation of β2AR by ISO inhibited insulin signalling, and the effect was primarily through the cAMP-PKA-JNK pathway and MEK/JNK signaling pathway. Yeast two-hybrid, co-immunoprecipitation and His-tag pull-down assay revealed that β2AR, IR, insulin receptor substrate 1 (IRS1), Grb2-associated binding protein 1 (GAB1) and Grb2 existed in the same protein complex.

CONCLUSION

The sustained stimulation of β2AR might inhibit insulin signaling transduction through the cAMP-PKA-JNK and MEK/JNK pathways in H9C2 cells.

Increased comparability between RNA-Seq and microarray data by utilization of gene sets

The field of transcriptomics uses and measures mRNA as a proxy of gene expression. There are currently two major platforms in use for quantifying mRNA, microarray and RNA-Seq. Many comparative studies have shown that their results are not always consistent. In this study we aim to find a robust method to increase comparability of both platforms enabling data analysis of merged data from both platforms. We transformed high dimensional transcriptomics data from two different platforms into a lower dimensional, and biologically relevant dataset by calculating enrichment scores based on gene set collections for all samples. We compared the similarity between data from both platforms based on the raw data and on the enrichment scores. We show that the performed data transforms the data in a biologically relevant way and filters out noise which leads to increased platform concordance. We validate the procedure using predictive models built with microarray based enrichment scores to predict subtypes of breast cancer using enrichment scores based on sequenced data. Although microarray and RNA-Seq expression levels might appear different, transforming them into biologically relevant gene set enrichment scores significantly increases their correlation, which is a step forward in data integration of the two platforms. The gene set collections were shown to contain biologically relevant gene sets. More in-depth investigation on the effect of the composition, size, and number of gene sets that are used for the transformation is suggested for future research.

The field of transcriptomics uses and measures mRNA as a proxy of gene expression. There are currently two major platforms in use for quantifying mRNA, microarray and RNA-Seq. Many comparative studies have shown that their results are not always consistent. In this study we aim to find a robust method to increase comparability of both platforms enabling data analysis of merged data from both platforms. We transformed the high dimensional transcriptomics data from the two different platforms into lower dimensional, and biologically relevant gene set scores. These gene sets were defined a-priori as specific combination of genes (e.g. up-regulated in a certain pathway). We observed that although microarray and RNA-Seq expression levels might appear different, using these gene sets to transform the data significantly increases their correlation. This is a step forward in data integration of the two platforms. More in-depth investigation on the effect of the composition, size, and number of gene sets that are used for the transformation is suggested for future research.

Codon usage pattern and evolutionary forces of mitochondrial ND genes among orders of class Amphibia

In this study, we used a bioinformatics approach to analyze the nucleotide composition and pattern of synonymous codon usage in mitochondrial ND genes in three amphibian groups, that is, orders Anura, Caudata, and Gymnophiona to identify the commonality and the differences of codon usage as no research work was reported yet. The high value of the effective number of codons revealed that the codon usage bias (CUB) was low in mitochondrial ND genes among the orders. Nucleotide composition analysis suggested that for each gene, the compositional features differed among Anura, Caudata, and Gymnophiona and the GC content was lower than AT content. Furthermore, a highly significant difference (p < .05) for GC content was found in each gene among the orders. The heat map showed contrasting patterns of codon usage among different ND genes. The regression of GC12 on GC3 suggested a narrow range of GC3 distribution and some points were located in the diagonal, indicating both mutation pressure and natural selection might influence the CUB. Moreover, the slope of the regression line was less than 0.5 in all ND genes among orders, indicating natural selection might have played the dominant role whereas mutation pressure had played a minor role in shaping CUB of ND genes across orders.

Comparison Between Expression Microarrays and RNA-Sequencing Using UKBEC Dataset Identified a trans-eQTL Associated with MPZ Gene in Substantia Nigra

In recent years, the advantages of RNA-sequencing (RNA-Seq) have made it the platform of choice for measuring gene expression over traditional microarrays. However, RNA-Seq comes with bioinformatical challenges and higher computational costs. Therefore, this study set out to assess whether the increased depth of transcriptomic information facilitated by RNA-Seq is worth the increased computation over microarrays, specifically at three levels: absolute expression levels, differentially expressed genes identification, and expression QTL (eQTL) mapping in regions of the human brain. Using the United Kingdom Brain Expression Consortium (UKBEC) dataset, there is high agreement of gene expression levels measured by microarrays and RNA-seq when quantifying absolute expression levels and when identifying differentially expressed genes. These findings suggest that depending on the aims of a study, the relative ease of working with microarray data may outweigh the computational time and costs of RNA-Seq pipelines. On the other, there was low agreement when mapping eQTLs. However, a number of eQTLs associated with genes that play important roles in the brain were found in both platforms. For example, a trans-eQTL was mapped that is associated with the MPZ gene in the substantia nigra. These eQTLs that we have highlighted are extremely promising candidates that merit further investigation.

Transcriptome-based selection and validation of optimal house-keeping genes for skin research in goats (Capra hircus)

BACKGROUND

In quantitative real-time polymerase chain reaction (qRT-PCR) experiments, accurate and reliable target gene expression results are dependent on optimal amplification of house-keeping genes (HKGs). RNA-seq technology offers a novel approach to detect new HKGs with improved stability. Goat (Capra hircus) is an economically important livestock species and plays an indispensable role in the world animal fiber and meat industry. Unfortunately, uniform and reliable HKGs for skin research have not been identified in goat. Therefore, this study seeks to identify a set of stable HKGs for the skin tissue of C. hircus using high-throughput sequencing technology.

RESULTS

Based on the transcriptome dataset of 39 goat skin tissue samples, 8 genes (SRP68, NCBP3, RRAGA, EIF4H, CTBP2, PTPRA, CNBP, and EEF2) with relatively stable expression levels were identified and selected as new candidate HKGs. Commonly used HKGs including SDHA and YWHAZ from a previous study, and 2 conventional genes (ACTB and GAPDH) were also examined. Four different experimental variables: (1) different development stages, (2) hair follicle cycle stages, (3) breeds, and (4) sampling sites were used for determination and validation. Four algorithms (geNorm, NormFinder, BestKeeper, and ΔCt method) and a comprehensive algorithm (ComprFinder, developed in-house) were used to assess the stability of each HKG. It was shown that NCBP3 + SDHA + PTPRA were more stably expressed than previously used genes in all conditions analysis, and that this combination was effective at normalizing target gene expression. Moreover, a new algorithm for comprehensive analysis, ComprFinder, was developed and released.

CONCLUSION

This study presents the first list of candidate HKGs for C. hircus skin tissues based on an RNA-seq dataset. We propose that the NCBP3 + SDHA + PTPRA combination could be regarded as a triplet set of HKGs in skin molecular biology experiments in C. hircus and other closely related species. In addition, we also encourage researchers who perform candidate HKG evaluations and who require comprehensive analysis to adopt our new algorithm, ComprFinder.

Spaceflight induces novel regulatory responses in Arabidopsis seedling as revealed by combined proteomic and transcriptomic analyses

BACKGROUND

Understanding of gravity sensing and response is critical to long-term human habitation in space and can provide new advantages for terrestrial agriculture. To this end, the altered gene expression profile induced by microgravity has been repeatedly queried by microarray and RNA-seq experiments to understand gravitropism. However, the quantification of altered protein abundance in space has been minimally investigated.

RESULTS

Proteomic (iTRAQ-labelled LC-MS/MS) and transcriptomic (RNA-seq) analyses simultaneously quantified protein and transcript differential expression of three-day old, etiolated Arabidopsis thaliana seedlings grown aboard the International Space Station along with their ground control counterparts. Protein extracts were fractionated to isolate soluble and membrane proteins and analyzed to detect differentially phosphorylated peptides. In total, 968 RNAs, 107 soluble proteins, and 103 membrane proteins were identified as differentially expressed. In addition, the proteomic analyses identified 16 differential phosphorylation events. Proteomic data delivered novel insights and simultaneously provided new context to previously made observations of gene expression in microgravity. There is a sweeping shift in post-transcriptional mechanisms of gene regulation including RNA-decapping protein DCP5, the splicing factors GRP7 and GRP8, and AGO4,. These data also indicate AHA2 and FERONIA as well as CESA1 and SHOU4 as central to the cell wall adaptations seen in spaceflight. Patterns of tubulin-α 1, 3,4 and 6 phosphorylation further reveal an interaction of microtubule and redox homeostasis that mirrors osmotic response signaling elements. The absence of gravity also results in a seemingly wasteful dysregulation of plastid gene transcription.

CONCLUSIONS

The datasets gathered from Arabidopsis seedlings exposed to microgravity revealed marked impacts on post-transcriptional regulation, cell wall synthesis, redox/microtubule dynamics, and plastid gene transcription. The impact of post-transcriptional regulatory alterations represents an unstudied element of the plant microgravity response with the potential to significantly impact plant growth efficiency and beyond. What's more, addressing the effects of microgravity on AHA2, CESA1, and alpha tubulins has the potential to enhance cytoskeletal organization and cell wall composition, thereby enhancing biomass production and growth in microgravity. Finally, understanding and manipulating the dysregulation of plastid gene transcription has further potential to address the goal of enhancing plant growth in the stressful conditions of microgravity.

Comparative transcriptome analysis of transcultured human skin-derived precursors (tSKPs) from adherent monolayer culture system and tSKPs-derived fibroblasts (tFBs) by RNA-Seq

Transcultured human skin derived precursors (tSKPs) from adherent monolayer culture system have similar characteristics as traditional skin derived precursors (SKPs), making tSKPs a suitable candidate for regenerative medicine. tSKPs can differentiate into fibroblasts. However, little is known about the molecular mechanism of the transition from tSKPs to fibroblasts. Here, we compared the transcriptional profiles of human tSKPs and tSKPs-derived fibroblasts (tFBs) by RNA-Sequence aiming to determine the candidate genes and pathways involving in the differentiation process. A total of 1042 differentially expressed genes (DEGs) were identified between tSKPs and tFBs, with 490 genes up-regulated and 552 genes down-regulated. Our study showed that these DEGs were significantly enriched in tumor necrosis factor signaling pathway, focal adhesion, extracellular matrix-receptor interaction and phosphatidylinositol 3 kinase (PI3K)/protein kinase B (Akt) signaling pathway. A further transcription factors (TFs) analysis of DEGs revealed the significantly down-expressed TFs (p21, Foxo1and Foxc1) in tFBs were mostly the downstream nodes of PI3K-Akt signaling pathway, which suggested PI3K-Akt signaling pathway might play an important role in tSKPs differentiation. The results of our study are useful for investigating the molecular mechanisms in tSKPs differentiation into tFBs, making it possible to take advantage of their potential application in regenerative medicine.

Comparison of defense responses of transgenic potato lines expressing three different Rpi genes to specific Phytophthora infestans races based on transcriptome profiling

Potato late blight, one of the most devastating diseases in potato, is caused by the oomycete Phytophthora infestans. Over 20 resistance genes have been cloned including R1, R3a, and R3b. The distinctions between defense response mechanisms mediated by different resistance genes are still unclear. Here we performed transcriptome profiling in three transgenic lines, R1, R3a, and R3b, and wild-type Desiree under inoculation with two P. infestans isolates, 89148 (race 0) and CN152 (super race), using RNA-seq. Compared with wild type, specific differentially expressed genes (DEGs) were identified in the three transgenic lines. The highest number of DEGs occurred in transgenic R3b, with 779 DEGs in response to isolate 89148 and 864 DEGs in response to infection by CN152, followed by transgenic R1 lines with 408 DEGs for isolate 89148 and 267 DEGs for CN152. Based on gene ontology, the most common GO terms (15 for 89148 and 20 for CN152) were enriched in transgenic R3a and R3b lines. This indicates that the defense pathways mediated by R3a and R3b are more similar than those mediated by R1. Further separate GO analysis of up- or down-regulated DEGs showed that the down-regulated DEGs mainly functioned in mediating the resistance of potato to P. infestans 89148 by response to stress biological process and to CN152 by oxidation reduction biological process. KEGG pathways of DNA replication, plant-pathogen interaction and pentose and glucuronate interconversions are unique for transgenic R1, R3a, and R3b lines in incompatible interactions. Quantitative real-time PCR experimental validation confirmed the induced expression of DEGs in the late blight resistance signaling pathway. Our results will lay a solid foundation for further understanding the mechanisms of plant-pathogen interactions, and provide a theoretical reference for durable resistance in potato.

Transcriptomic and Proteomic Tools in the Study of Hg Toxicity: What Is Missing?

Mercury is a hazardous substance that has unique neurodevelopmental toxic effects in humans. However, the precise sequence of molecular events that culminate in Hg-induced neuropathology is still unknown. Though the omics studies have been generating an enormous amount of new data about Hg toxicity, our ability to interpret such a large quantity of information is still limited. In this opinion article, we will reinforce the necessity of new high throughput and accurate analytical proteomic methodologies, especially, thiol and selenol-proteome. Overall, we posit that improvements in thiol- and selenol-proteomic analyses will be pivotal in identifying the primary cellular targets of Hg. However, a better understanding of the complex cascades and molecular pathways involved in its toxicity will require extensive complementary studies in more complex systems.

Systems Vaccinology for a Live Attenuated Tularemia Vaccine Reveals Unique Transcriptional Signatures That Predict Humoral and Cellular Immune Responses

Background: Tularemia is a potential biological weapon due to its high infectivity and ease of dissemination. This study aimed to characterize the innate and adaptive responses induced by two different lots of a live attenuated tularemia vaccine and compare them to other well-characterized viral vaccine immune responses. Methods: Microarray analyses were performed on human peripheral blood mononuclear cells (PBMCs) to determine changes in transcriptional activity that correlated with changes detected by cellular phenotyping, cytokine signaling, and serological assays. Transcriptional profiles after tularemia vaccination were compared with yellow fever [YF-17D], inactivated [TIV], and live attenuated [LAIV] influenza. Results: Tularemia vaccine lots produced strong innate immune responses by Day 2 after vaccination, with an increase in monocytes, NK cells, and cytokine signaling. T cell responses peaked at Day 14. Changes in gene expression, including upregulation of STAT1, GBP1, and IFIT2, predicted tularemia-specific antibody responses. Changes in CCL20 expression positively correlated with peak CD8+ T cell responses, but negatively correlated with peak CD4+ T cell activation. Tularemia vaccines elicited gene expression signatures similar to other replicating vaccines, inducing early upregulation of interferon-inducible genes. Conclusions: A systems vaccinology approach identified that tularemia vaccines induce a strong innate immune response early after vaccination, similar to the response seen after well-studied viral vaccines, and produce unique transcriptional signatures that are strongly correlated to the induction of T cell and antibody responses.

Normalization Methods for the Analysis of Unbalanced Transcriptome Data: A Review

Dozens of normalization methods for correcting experimental variation and bias in high-throughput expression data have been developed during the last two decades. Up to 23 methods among them consider the skewness of expression data between sample states, which are even more than the conventional methods, such as loess and quantile. From the perspective of reference selection, we classified the normalization methods for skewed expression data into three categories, data-driven reference, foreign reference, and entire gene set. We separately introduced and summarized these normalization methods designed for gene expression data with global shift between compared conditions, including both microarray and RNA-seq, based on the reference selection strategies. To our best knowledge, this is the most comprehensive review of available preprocessing algorithms for the unbalanced transcriptome data. The anatomy and summarization of these methods shed light on the understanding and appropriate application of preprocessing methods.

Transcriptome dynamics of alternative splicing events revealed early phase of apoptosis induced by methylparaben in H1299 human lung carcinoma cells

Methylparaben is most frequently used as an antimicrobial preservative in pharmaceuticals and foods. Methylparaben has been subjected to toxicological studies owing to the increasing concern regarding its possible impact on the environment and human health. However, the cytotoxicity and underlying mechanisms of methylparaben exposure in human lung cells have not been explored. Here, we investigated the effect of methylparaben on cell cycle, apoptotic pathways, and changes in the transcriptome profiles in human lung cells. Our results demonstrate that treatment with methylparaben causes inhibition of cell growth. In addition, methylparaben induced S- and G2/M-phase arrest as a result of enhanced apoptosis. Transcriptome analysis using RNA-seq revealed that mRNA expression of ER stress- and protein misfolding-related gene sets was upregulated in methylparaben-treated group. RNA splicing- and maturation-related gene sets were significantly down-regulated by methylparaben treatment. Interestingly, RNA-seq analysis at the transcript level revealed that alternative splicing events, especially retained intron, were markedly changed by a low dose of methylparaben treatment. Altogether, these data show that methylparaben induces an early phase of apoptosis through cell cycle arrest and downregulation of mRNA maturation.

Deciphering signalling network in broad spectrum Near Isogenic Lines of rice resistant to Magnaporthe oryzae

Disease resistance (R) genes like Pi9, Pita, Pi21, Pi54 are playing important role for broad spectrum blast resistance in rice. Development of near isogenic lines (NILs) using these type of broad spectrum genes and understanding their signalling networks is essential to cope up with highly evolving Magnaporthe oryzae strains for longer duration. Here, transcriptional-level changes were studied in three near-isogenic lines (PB1 + Pi1, PB1 + Pi9 and PB1 + Pi54) of rice resistant to blast infection, to find the loci that are unique to resistant lines developed in the background of Pusa Basmati 1 (PB1). The pathway analysis of loci, unique to resistant NILs compared to susceptible control revealed that plant secondary metabolite synthesis was the common mechanism among all NILs to counter against M. oryzae infection. Comparative transcriptome analysis helped to find out common clusters of co-expressed significant differentially expressed loci (SDEL) in both PB1 + Pi9 and PB1 + Pi54 NILs. SDELs from these clusters were involved in the synthesis and degradation of starch; synthesis and elongation of fatty acids; hydrolysis of phospholipids; synthesis of phenylpropanoid; and metabolism of ethylene and jasmonic acid. Through detailed analysis of loci specific to each resistant NIL, we identified a network of signalling pathways mediated by each blast resistance gene. The study also offers insights into transcriptomic dynamics, points to a set of important candidate genes that serve as module to regulate the changes in resistant NILs. We suggest that pyramiding of the blast resistance gene Pi9 with Pi54 will lead to maximum broad spectrum resistance to M. oryzae.

Chikungunya virus modulates the miRNA expression patterns in human synovial fibroblasts

Chikungunya virus (CHIKV) is an alphavirus transmitted by mosquitoes. CHIKV infection leads to polyarthritis and polyarthralgia among patients. The synovial fibroblasts are the primary target for CHIKV. The microRNAs (miRNAs) are the small endogenous noncoding RNAs which posttranscriptionally regulate the expression of genes by binding to their target messenger RNAs (mRNAs) through their 3'-untranslated regions. The miRNAs are the key regulators for various pathological processes including viral infection, cancer, cardiovascular disease, and neurodegeneration. This study was designed to dissect out the roles of miRNAs during CHIKV (Ross Strain E1: A226V) infection in primary human synovial fibroblasts. The miRNA microarray profiling was performed on the primary human synovial fibroblasts infected by CHIKV. The gene target prediction analysis, enrichment, and network analysis were performed by various bioinformatics analyses. The subset of 26 differentially expressed microRNAs (DEMs) were identified through microarray profiling and were further screened for gene predictions, Gene Ontology, pathway enrichment, and miRNA-mRNA network using various bioinformatics tools. The bioinformatics analysis indicates the role of DEMs by suppressing the immune response which may contribute to CHIKV persistence in human primary synovial fibroblasts. Our study provides the plausible roles of DEMs, miRNAs, and mRNA interactions and pathways involved in the molecular pathogenesis of CHIKV.

Omics Application of Bio-Hydrogen Production Through Green Alga Chlamydomonas reinhardtii

This article summarizes the current knowledge regarding omics approaches, which include genomics, transcriptomics, proteomics and metabolomics, in the context of bio-hydrogen production in Chlamydomonas reinhardtii. In this paper, critical genes (HydA1, Hyd A2, Sulp, Tla1, Sta7, PFL1) involved in H₂ metabolism were identified and analyzed for their function in H₂ accumulation. Furthermore, the advantages of gene microarrays and RNA-seq were compared, as well as their applications in transcriptomic analysis of H₂ production. Moreover, as a useful tool, proteomic analysis could identify different proteins that participate in H₂ metabolism. This review provides fundamental theory and an experimental basis for H₂ production, and further research effort is needed in this field.

Dihydroartemisinin suppresses glycolysis of LNCaP cells by inhibiting PI3K/AKT pathway and downregulating HIF-1α expression

AIMS

Dihydroartemisinin (DHA) exhibits potential anticancer activity. However, the biological functions of DHA in prostate cancer remain largely unexplored. In this study, we aim to investigate the anti-proliferative effect and glycolysis regulation of DHA on prostate cancer cell LNCaP.

MAIN METHODS

Cell proliferative activity and apoptosis inducing were detected. The gene expression was detected by mRNA microarray and results were analyzed by GO and KEGG pathway database. Expressions of glycolysis key enzymes and PI3K/AKT/HIF-1α were detected by Western blot.

KEY FINDINGS

Results indicated that DHA could inhibit the LNCaP cell proliferation considerably and induce cell apoptosis. mRNA microarray showed 1293 genes were upregulated and 2322 genes were downregulated. GO and KEGG enrichment analysis suggested that glycolysis pathway was correlated with DHA inhibited the proliferation on the LNCaP cell. Western blot results showed that DHA can decrease GLUT1 and regulatory enzymes of glycolytic pathway expression probably by suppressing the activity of the intracellular Akt/mTOR and HIF-1 α.

SIGNIFICANCE

Experimental validation results indicate that DHA treatment can inhibit the LNCaP cell proliferation and induce apoptosis, which may be related to glycolysis inhibition.

Bioinformatic analysis of bacteria and host cell dual RNA-sequencing experiments

Bacterial pathogens subvert host cells by manipulating cellular pathways for survival and replication; in turn, host cells respond to the invading pathogen through cascading changes in gene expression. Deciphering these complex temporal and spatial dynamics to identify novel bacterial virulence factors or host response pathways is crucial for improved diagnostics and therapeutics. Dual RNA sequencing (dRNA-Seq) has recently been developed to simultaneously capture host and bacterial transcriptomes from an infected cell. This approach builds on the high sensitivity and resolution of RNA sequencing technology and is applicable to any bacteria that interact with eukaryotic cells, encompassing parasitic, commensal or mutualistic lifestyles. Several laboratory protocols have been presented that outline the collection, extraction and sequencing of total RNA for dRNA-Seq experiments, but there is relatively little guidance available for the detailed bioinformatic analyses required. This protocol outlines a typical dRNA-Seq experiment, based on a Chlamydia trachomatis-infected host cell, with a detailed description of the necessary bioinformatic analyses with currently available software tools.

Comparative Analysis of Brain and Fat Body Gene Splicing Patterns in the Honey Bee, Apis mellifera

RNA-seq has proven to be a powerful tool to unravel various aspects of the transcriptome, especially the quantification of alternative splicing (AS) that leads to isoform diversity. The honey bee (Apis mellifera) is an important model organism for studying the molecular underpinnings of behavioral plasticity and social behavior, and recent RNA-seq studies of honey bees have revealed AS patterns and their regulation by DNA methylation. However, tissue-specific AS patterns have not been fully explored. In this paper, we characterized AS patterns in two different honey bee tissue types, and also explored their conservation and regulation. We used the RNA-seq data from brain and fat body to improve the existing models of honey bee genes and identified tissue-specific AS patterns. We found that AS genes show high conservation between honey bee and Drosophila melanogaster. We also confirmed and extended previous findings of a correlation between gene body DNA methylation and AS patterns, providing further support for the role of DNA methylation in regulating AS. In addition, our analysis suggests distinct functional roles for tissue-specific alternatively spliced genes. Taken together, our work provides new insights into the conservation and dynamics of AS patterns across different tissue types.

The Kinome of Human Alveolar Type II and Basal Cells, and Its Reprogramming in Lung Cancer

The discovery of mutant tyrosine kinases as oncogenic drivers of lung adenocarcinomas has changed the basic understanding of lung cancer development and therapy. Yet, expressed kinases (kinome) in lung cancer progenitor cells, as well as whether kinase expression and the overall kinome changes or is reprogrammed upon transformation, is incompletely understood. We hypothesized that the kinome differs between lung cancer progenitor cells, alveolar type II cells (ATII), and basal cells (BC) and that their respective kinomes undergo distinct lineage-specific reprogramming to adenocarcinomas and squamous cell carcinomas upon transformation. We performed RNA sequencing on freshly isolated human ATII, BC, and lung cancer cell lines to define the kinome in nontransformed cells and transformed cells. Our studies identified a unique kinome for ATII and BC and changes in their kinome upon transformation to their respective carcinomas.

Interrogation of Milk-Driven Changes to the Proteome of Intestinal Epithelial Cells by Integrated Proteomics and Glycomics

Bovine colostrum is a rich source of bioactive components which are important in the development of the intestine, in stimulating gut structure and function and in preparing the gut surface for subsequent colonization of microbes. What is not clear, however, is how colostrum may affect the repertoire of receptors and membrane proteins of the intestinal surface and the post-translational modifications associated with them. In the present work, we aimed to characterize the surface receptor and glycan profile of human HT-29 intestinal cells after exposure to a bovine colostrum fraction (BCF) by means of proteomic and glycomic analyses. Integration of label-free quantitative proteomic analysis and lectin array profiles confirmed that BCF exposure results in changes in the levels of glycoproteins present at the cell surface and also changes to their glycosylation pattern. This study contributes to our understanding of how milk components may regulate intestinal cells and prime them for bacterial interaction.

Host Transcriptomics as a Tool to Identify Diagnostic and Mechanistic Immune Signatures of Tuberculosis

Tuberculosis (TB) is a major infectious disease worldwide, and is associated with several challenges for control and eradication. First, more accurate diagnostic tools that better represent the spectrum of infection states are required; in particular, identify the latent TB infected individuals with high risk of developing active TB. Second, we need to better understand, from a mechanistic point of view, why the immune system is unsuccessful in some cases for control and elimination of the pathogen. Host transcriptomics is a powerful approach to identify both diagnostic and mechanistic immune signatures of diseases. We have recently reported that optimal study design for these two purposes should be guided by different sets of criteria. Here, based on already published transcriptomics signatures of tuberculosis, we further develop these guidelines and identify additional factors to consider for obtaining diagnostic vs. mechanistic signatures in terms of cohorts, samples, data generation and analysis. Diagnostic studies should aim to identify small disease signatures with high discriminatory power across all affected populations, and against similar pathologies to TB. Specific focus should be made on improving the diagnosis of infected individuals at risk of developing active disease. Conversely, mechanistic studies should focus on tissues biopsies, immune relevant cell subsets, state of the art transcriptomic techniques and bioinformatics tools to understand the biological meaning of identified gene signatures that could facilitate therapeutic interventions. Finally, investigators should ensure their data are made publicly available along with complete annotations to facilitate metadata and cross-study analyses.

Analysis of Developing Rice Grain Transcriptome Using the Agilent Microarray Platform

Transcriptome analysis reflects the status quo of transcribed genetic code present in the form of mRNA, which helps to infer biological processes and unravel metabolic status. Despite the increasing adoption of RNA-Seq technique in recent years, transcriptome analysis using the microarray platform remains the gold standard technique, which offers a simpler, more cost-effective, and efficient method for high-throughput gene expression profiling. In this chapter, we described a streamlined transcriptomic analyses pipeline employed to study developing rice grains that can also be applied to other tissue samples and species. We described a novel RNA extraction method that obviates the problem introduced by high-starch content during rice grain development that usually leads to reduction in RNA yield and quality. The detailed procedure of microarray analysis involved in cDNA synthesis, cRNA labeling, microarray hybridization, slide scanning, feature extraction to QC validation has been described. The description of a newly developed Indica- and Japonica-specific microarray slides developed from the genome information of subpopulation to study gene expression of 60,000 genes has been highlighted. The downstream bioinformatics analyses including expression QTL mapping and gene regulatory network analyses were mentioned.

Varying dietary protein and fat elicits differential transcriptomic expression within stress response pathways in preweaned Holstein heifers

Increases in milk replacer dietary energy subsequently increase growth and weight in preweaned dairy heifers. However, the underlying effects of dietary component increases on key functional pathways have yet to be fully investigated. Elucidating these relationships may provide insights into the mechanisms through which protein and fat are partitioned for tissue growth and metabolism. We hypothesized that genes within key growth and metabolic pathways would be differentially expressed between calves fed a protein- and fat-restricted diet and calves fed a protein- and fat-enhanced diet. The objectives of this study were to (1) identify genes differentially expressed between dietary restricted calves and enhanced calves and (2) determine the key regulatory pathways influenced by these genes. Preweaned Holstein heifers (n = 12; 6 ± 0.02 d of age) were randomly assigned to 1 of 2 milk replacer diets: enhanced (28.9% crude protein, 26.2% fat; n = 6) or restricted (20.9% crude protein, 19.8% fat; n = 6). Growth measures included average daily gain and gain-to-feed ratio. After 56 d, calves were killed for tissue collection. Samples from longissimus dorsi, adipose, and liver tissues were collected and RNA was isolated for RNA sequencing analysis. The MIXED procedure of SAS (SAS Institute Inc., Cary, NC) was used to evaluate relationships of growth with dietary energy. Fixed effects included date of collection and time (day). Random effects included sire and birth weight. The RNA sequencing analysis was performed using CLC Genomics Workbench (Qiagen, Germantown, MD), and the Robinson and Smith exact test was used to identify differentially expressed genes between diets. The Protein Analysis Through Evolutionary Relationships (PANTHER) database was then used to identify functional categories of differentially expressed genes. Enhanced calves had increased growth rates and feed efficiency compared with restricted calves (average daily gain = 0.76 and 0.22, respectively; gain-to-feed ratio = 0.10 and 0.06, respectively). There were 238 differentially expressed genes in adipose, 227 in longissimus dorsi, and 40 in liver. We identified 10 genes concordant among tissues. As expected, functional analyses suggested that the majority of genes were associated with metabolic or cellular processes, predominantly cell communication and cell cycle. Overall, it appears that varying levels of dietary protein and fat influence calf growth and development through metabolic processes, including oxidative phosphorylation and glyceroneogenesis. However, protein- and fat-restricted calves appeared to experience metabolic stress at a cellular level, as evidenced by an upregulation in stress response pathways, including genes in the p53 pathway. Calves could be fed at a higher level of protein and fat to decrease the prevalence of metabolic stress at the cellular level, but evidence indicating the presence of inflammatory stress and adipose fibrosis in enhanced calves prompts further investigation of the effects of milk replacer component levels.

Assessment of Bioleaching Microbial Community Structure and Function Based on Next-Generation Sequencing Technologies

It is widely known that bioleaching microorganisms have to cope with the complex extreme environment in which microbial ecology relating to community structure and function varies across environmental types. However, analyses of microbial ecology of bioleaching bacteria is still a challenge. To address this challenge, numerous technologies have been developed. In recent years, high-throughput sequencing technologies enabling comprehensive sequencing analysis of cellular RNA and DNA within the reach of most laboratories have been added to the toolbox of microbial ecology. The next-generation sequencing technology allowing processing DNA sequences can produce available draft genomic sequences of more bioleaching bacteria, which provides the opportunity to predict models of genetic and metabolic potential of bioleaching bacteria and ultimately deepens our understanding of bioleaching microorganism. High-throughput sequencing that focuses on targeted phylogenetic marker 16S rRNA has been effectively applied to characterize the community diversity in an ore leaching environment. RNA-seq, another application of high-throughput sequencing to profile RNA, can be for both mapping and quantifying transcriptome and has demonstrated a high efficiency in quantifying the changing expression level of each transcript under different conditions. It has been demonstrated as a powerful tool for dissecting the relationship between genotype and phenotype, leading to interpreting functional elements of the genome and revealing molecular mechanisms of adaption. This review aims to describe the high-throughput sequencing approach for bioleaching environmental microorganisms, particularly focusing on its application associated with challenges.

TISSUES 2.0: an integrative web resource on mammalian tissue expression

Physiological and molecular similarities between organisms make it possible to translate findings from simpler experimental systems—model organisms—into more complex ones, such as human. This translation facilitates the understanding of biological processes under normal or disease conditions. Researchers aiming to identify the similarities and differences between organisms at the molecular level need resources collecting multi-organism tissue expression data. We have developed a database of gene–tissue associations in human, mouse, rat and pig by integrating multiple sources of evidence: transcriptomics covering all four species and proteomics (human only), manually curated and mined from the scientific literature. Through a scoring scheme, these associations are made comparable across all sources of evidence and across organisms. Furthermore, the scoring produces a confidence score assigned to each of the associations. The TISSUES database (version 2.0) is publicly accessible through a user-friendly web interface and as part of the STRING app for Cytoscape. In addition, we analyzed the agreement between datasets, across and within organisms, and identified that the agreement is mainly affected by the quality of the datasets rather than by the technologies used or organisms compared.

Database URL: http://tissues.jensenlab.org/

Next generation sequencing analysis of soy glyceollins and 17-β estradiol: Effects on transcript abundance in the female mouse brain

Glyceollins (Glys) are produced by soy plants in response to stress and are known for their anti-estrogenic activity both in vivo and in vitro in cancer cell lines as well as peripheral tissues. Glys can also exhibit non-estrogen receptor (ER) mediated effects. The effects of Glys on gene expression in the brain are still unclear. For this study, 17-β estradiol (E2) or placebo slow-release pellets were implanted into ovariectomized CFW mice followed by 11 days of exposure to either Glys or vehicle i.p. injections. We then examined the female mouse brain transcriptome using paired-end RNA sequencing (RNA-Seq) on the Illumina GAIIx platform. The goal of this study was to compare and contrast the results obtained from RNA-Seq with the results from our previous whole brain microarray experiment, which indicated that Glys potentially act through both ER-mediated and non-ER-mediated mechanisms, exhibiting a gene expression profile distinct from E2-treated groups. Our results suggest that the transcripts regulated by both E2 and Glys alone or in combination annotated to similar pathway maps and networks in both microarray and RNA-Seq experiments. Additionally, unlike our microarray data analysis, RNA-Seq enabled the detection of treatment effects on low expression transcripts of interest (e.g., prolactin and growth hormone). Collectively, our results suggest that depending on the gene, Glys can regulate expression independently of E2 action, similarly to E2, or oppose E2's effects in the female mouse brain.

Bioinformatics Analysis of Transcriptomic Data Reveals Refined Functional Networks for the Self-Renewal of Mouse Spermatogonial Stem Cells

Spermatogonial stem cells (SSCs) are exquisitely regulated to reach a balance between proliferation and differentiation in the niche of seminiferous epithelium. Several extrinsic factors such as GDNF are reported to switch the transition, activating various intrinsic signaling pathways. Transcriptomics analysis could provide a comprehensive landscape of gene expression and regulation. Here, we reanalyzed a previously published transcriptome of two cell types (standing for self-renewing and differentiating SSCs correspondingly). First, we proposed a new parameter, the expression index, to sort the genes considering both absolute and relative expression levels. Using a dynamic statistical model, we identified a list of 1119 candidate genes for SSC self-renewal with the best enrichment of canonical markers. Finally, based on interaction relations, we further optimized the list and constructed a refined network containing integrated information of interactions, expression alternations, biological functions, and disease associations. Further annotation of the 521 refined genes involved in the network revealed an enrichment of well-studied signaling pathways. We believe that the refined network could help us better understand the regulation of SSCs' fates, as well as find novel regulators or targets for SSC self-renewal or preservation of male fertility.

RNA sequencing to predict response to TNF-α inhibitors reveals possible mechanism for nonresponse in smokers

BACKGROUND

Several studies have employed microarray-based profiling to predict response to tumor necrosis factor-alpha inhibitors (TNFi) in rheumatoid arthritis (RA); yet efforts to validate these targets have failed to show predictive abilities acceptable for clinical practice.

METHODS

The eighty most extreme responders and nonresponders to TNFi therapy were selected from the observational BiOCURA cohort. RNA sequencing was performed on mRNA from peripheral blood mononuclear cells (PBMCs) collected before initiation of treatment. The expression of pathways as well as individual gene transcripts between responders and nonresponders was investigated. Promising targets were technically replicated and validated in n = 40 new patients using qPCR assays.

RESULTS

Before therapy initiation, nonresponders had lower expression of pathways related to interferon and cytokine signaling, while also showing higher levels of two genes, GPR15 and SEMA6B (p = 0.02). The two targets could be validated, however, additional analyses revealed that GPR15 and SEMA6B did not independently predict response, but were rather dose-dependent markers of smoking (p < 0.0001).

CONCLUSIONS

The study did not identify new transcripts ready to use in clinical practice, yet GPR15 and SEMA6B were recognized as candidate explanatory markers for the reduced treatment success in RA smokers.

Divergent and convergent evolution of housekeeping genes in human-pig lineage

Housekeeping genes are ubiquitously expressed and maintain basic cellular functions across tissue/cell type conditions. The present study aimed to develop a set of pig housekeeping genes and compare the structure, evolution and function of housekeeping genes in the human–pig lineage. By using RNA sequencing data, we identified 3,136 pig housekeeping genes. Compared with human housekeeping genes, we found that pig housekeeping genes were longer and subjected to slightly weaker purifying selection pressure and faster neutral evolution. Common housekeeping genes, shared by the two species, achieve stronger purifying selection than species-specific genes. However, pig- and human-specific housekeeping genes have similar functions. Some species-specific housekeeping genes have evolved independently to form similar protein active sites or structure, such as the classical catalytic serine–histidine–aspartate triad, implying that they have converged for maintaining the basic cellular function, which allows them to adapt to the environment. Human and pig housekeeping genes have varied structures and gene lists, but they have converged to maintain basic cellular functions essential for the existence of a cell, regardless of its specific role in the species. The results of our study shed light on the evolutionary dynamics of housekeeping genes.

Transcriptomic studies in tolerance: Lessons learned and the path forward

Immunosuppression after solid organ transplantation is a delicate balance of the immune response and is a complex phenomenon with many factors involved. Despite advances in the care of patients receiving organ transplants the adverse effects associated with immunosuppressive agents and the risks of long-term immunosuppression present a series of challenges and the need to weigh the risks and benefits of either over or under-immunosuppression. Ideally, if all transplant recipients could develop donor-specific immunological tolerance, it could drastically improve long-term graft survival without the need for immunosuppressive agents. In the absence of this ideal situation, the next best approach would be to develop tools to determine the adequacy of immunosuppression in each patient, in a manner that would individualize or personalize therapy. Despite current genomics-based studies of tolerance biomarkers in transplantation there are currently, no clinically validated tools to safely increase or decrease the level of IS that is beneficial to the patient. However, the successful identification of biomarkers and/or mechanisms of tolerance that have implications on long-term graft survival and outcomes depend on proper integration of study design, experimental protocols, and data-driven hypotheses. The objective of this article is to first, discuss the progress made on genomic biomarkers of immunological tolerance and the future avenues for the development of such biomarkers specifically in kidney transplantation. Secondly, we provide a set of guiding principles and identify the pitfalls, advantages, and drawbacks of studies that generate genomic data aimed at understanding transplant tolerance that is applicable to all solid transplants.

Functional Analysis of Mating Type Genes and Transcriptome Analysis during Fruiting Body Development of Botrytis cinerea

Botrytis cinerea is a plant-pathogenic fungus producing apothecia as sexual fruiting bodies. To study the function of mating type (MAT) genes, single-gene deletion mutants were generated in both genes of the MAT1-1 locus and both genes of the MAT1-2 locus. Deletion mutants in two MAT genes were entirely sterile, while mutants in the other two MAT genes were able to develop stipes but never formed an apothecial disk. Little was known about the reprogramming of gene expression during apothecium development. We analyzed transcriptomes of sclerotia, three stages of apothecium development (primordia, stipes, and apothecial disks), and ascospores by RNA sequencing. Ten secondary metabolite gene clusters were upregulated at the onset of sexual development and downregulated in ascospores released from apothecia. Notably, more than 3,900 genes were differentially expressed in ascospores compared to mature apothecial disks. Among the genes that were upregulated in ascospores were numerous genes encoding virulence factors, which reveals that ascospores are transcriptionally primed for infection prior to their arrival on a host plant. Strikingly, the massive transcriptional changes at the initiation and completion of the sexual cycle often affected clusters of genes, rather than randomly dispersed genes. Thirty-five clusters of genes were jointly upregulated during the onset of sexual reproduction, while 99 clusters of genes (comprising >900 genes) were jointly downregulated in ascospores. These transcriptional changes coincided with changes in expression of genes encoding enzymes participating in chromatin organization, hinting at the occurrence of massive epigenetic regulation of gene expression during sexual reproduction.IMPORTANCE Fungal fruiting bodies are formed by sexual reproduction. We studied the development of fruiting bodies ("apothecia") of the ubiquitous plant-pathogenic ascomycete Botrytis cinerea The role of mating type genes in apothecium development was investigated by targeted mutation. Two genes are essential for the initiation of sexual development; mutants in these genes are sterile. Two other genes were not essential for development of stipes; however, they were essential for stipes to develop a disk and produce sexual ascospores. We examined gene expression profiles during apothecium development, as well as in ascospores sampled from apothecia. We provide the first study ever of the transcriptome of pure ascospores in a filamentous fungus. The expression of numerous genes involved in plant infection was induced in the ascospores, implying that ascospores are developmentally primed for infection before their release from apothecia.

DART: a fast and accurate RNA-seq mapper with a partitioning strategy

MOTIVATION

In recent years, the massively parallel cDNA sequencing (RNA-Seq) technologies have become a powerful tool to provide high resolution measurement of expression and high sensitivity in detecting low abundance transcripts. However, RNA-seq data requires a huge amount of computational efforts. The very fundamental and critical step is to align each sequence fragment against the reference genome. Various de novo spliced RNA aligners have been developed in recent years. Though these aligners can handle spliced alignment and detect splice junctions, some challenges still remain to be solved. With the advances in sequencing technologies and the ongoing collection of sequencing data in the ENCODE project, more efficient alignment algorithms are highly demanded. Most read mappers follow the conventional seed-and-extend strategy to deal with inexact matches for sequence alignment. However, the extension is much more time consuming than the seeding step.

RESULTS

We proposed a novel RNA-seq de novo mapping algorithm, call DART, which adopts a partitioning strategy to avoid the extension step. The experiment results on synthetic datasets and real NGS datasets showed that DART is a highly efficient aligner that yields the highest or comparable sensitivity and accuracy compared to most state-of-the-art aligners, and more importantly, it spends the least amount of time among the selected aligners.

AVAILABILITY AND IMPLEMENTATION

https://github.com/hsinnan75/DART.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Advantages of RNA-seq compared to RNA microarrays for transcriptome profiling of anterior cruciate ligament tears

Microarrays and RNA-seq are at the forefront of high throughput transcriptome analyses. Since these methodologies are based on different principles, there are concerns about the concordance of data between the two techniques. The concordance of RNA-seq and microarrays for genome-wide analysis of differential gene expression has not been rigorously assessed in clinically derived ligament tissues. To demonstrate the concordance between RNA-seq and microarrays and to assess potential benefits of RNA-seq over microarrays, we assessed differences in transcript expression in anterior cruciate ligament (ACL) tissues based on time-from-injury. ACL remnants were collected from patients with an ACL tear at the time of ACL reconstruction. RNA prepared from torn ACL remnants was subjected to Agilent microarrays (N = 24) and RNA-seq (N = 8). The correlation of biological replicates in RNA-seq and microarrays data was similar (0.98 vs. 0.97), demonstrating that each platform has high internal reproducibility. Correlations between the RNA-seq data and the individual microarrays were low, but correlations between the RNA-seq values and the geometric mean of the microarrays values were moderate. The cross-platform concordance for differentially expressed transcripts or enriched pathways was linearly correlated (r = 0.64). RNA-Seq was superior in detecting low abundance transcripts and differentiating biologically critical isoforms. Additional independent validation of transcript expression was undertaken using microfluidic PCR for selected genes. PCR data showed 100% concordance (in expression pattern) with RNA-seq and microarrays data. These findings demonstrate that RNA-seq has advantages over microarrays for transcriptome profiling of ligament tissues when available and affordable. Furthermore, these findings are likely transferable to other musculoskeletal tissues where tissue collection is challenging and cells are in low abundance. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:484-497, 2018.

RNA-seq reveals transcriptome changes in goats following myostatin gene knockout

Myostatin (MSTN) is a powerful negative regulator of skeletal muscle mass in mammalian species that is primarily expressed in skeletal muscles, and mutations of its encoding gene can result in the double-muscling trait. In this study, the CRISPR/Cas9 technique was used to edit MSTN in Shaanbei Cashmere goats and generate knockout animals. RNA sequencing was used to determine and compare the transcriptome profiles of the muscles from three wild-type (WT) goats, three fibroblast growth factor 5 (FGF5) knockout goats (FGF5+/- group) and three goats with disrupted expression of both the FGF5 and MSTN genes (FM+/- group). The sequence reads were obtained using the Illumina HiSeq 2000 system and mapped to the Capra hircus reference genome using TopHat (v2.0.9). In total, 68.93, 62.04 and 66.26 million clean sequencing reads were obtained from the WT, FM+/- and FGF5+/- groups, respectively. There were 201 differentially expressed genes (DEGs) between the WT and FGF5+/- groups, with 86 down- and 115 up-regulated genes in the FGF5+/- group. Between the WT and FM+/- groups, 121 DEGs were identified, including 81 down- and 40 up-regulated genes in the FM+/- group. A total of 198 DEGs were detected between the FGF5+/- group and FM+/- group, with 128 down- and 70 up-regulated genes in the FM+/- group. At the transcriptome level, we found substantial changes in genes involved in fatty acid metabolism and the biosynthesis of unsaturated fatty acids, such as stearoyl-CoA dehydrogenase, 3-hydroxyacyl-CoA dehydratase 2, ELOVL fatty acid elongase 6 and fatty acid synthase, suggesting that the expression levels of these genes may be directly regulated by MSTN and that these genes are likely downstream targets of MSTN with potential roles in lipid metabolism in goats. Moreover, five randomly selected DEGs were further validated with qRT-PCR, and the results were consistent with the transcriptome analysis. The present study provides insight into the unique transcriptome profile of the MSTN knockout goat, which is a valuable resource for studying goat genomics.

Modifying SAMseq to account for asymmetry in the distribution of effect sizes when identifying differentially expressed genes

RNA-Seq is a developing technology for generating gene expression data by directly sequencing mRNA molecules in a sample. RNA-Seq data consist of counts of reads recorded to a particular gene that are often used to identify differentially expressed (DE) genes. A common statistical method used to analyze RNA-Seq data is Significance Analysis of Microarray with emphasis on RNA-Seq data (SAMseq). SAMseq is a nonparametric method that uses a resampling technique to account for differences in sequencing depths when identifying DE genes. We propose a modification of this method that takes into account asymmetry in the distribution of the effect sizes by taking into account the sign of the test statistics. Through simulation studies, we showthat the proposed method, comparedwith the traditional SAMseqmethod and other existing methods provides better power for identifying truly DE genes or more sufficiently controls FDR in most settings where asymmetry is present. We illustrate the use of the proposed method by analyzing an RNA-Seq data set containing C57BL/6J (B6) and DBA/2J (D2) mouse strains samples.

Intensive herbicide use has selected for constitutively elevated levels of stress-responsive mRNAs and proteins in multiple herbicide-resistant Avena fatua L

BACKGROUND

Intensive use of herbicides has led to the evolution of two multiple herbicide-resistant (MHR) Avena fatua (wild oat) populations in Montana that are resistant to members of all selective herbicide families available for A. fatua control in US small grain crops. We used transcriptome and proteome surveys to compare constitutive changes in MHR and herbicide-susceptible (HS) plants associated with non-target site resistance.

RESULTS

Compared to HS plants, MHR plants contained constitutively elevated levels of differentially expressed genes (DEGs) with functions in xenobiotic catabolism, stress response, redox maintenance and transcriptional regulation that are similar to abiotic stress-tolerant phenotypes. Proteome comparisons identified similarly elevated proteins including biosynthetic and multifunctional enzymes in MHR plants. Of 25 DEGs validated by RT-qPCR assay, differential regulation of 21 co-segregated with flucarbazone-sodium herbicide resistance in F₃ families, and a subset of 10 of these were induced or repressed in herbicide-treated HS plants.

CONCLUSION

Although the individual and collective contributions of these DEGs and proteins to MHR remain to be determined, our results support the idea that intensive herbicide use has selected for MHR populations with altered, constitutively regulated patterns of gene expression that are similar to those in abiotic stress-tolerant plants. © 2017 Society of Chemical Industry.