Variation in RNA-Seq transcriptome profiles of peripheral whole blood from healthy individuals with and without globin depletion

A pipeline for the development and analysis of extracellular vesicle-based transcriptomic biomarkers in molecular diagnostics

Extracellular vesicles are shed by every cell type and can be found in any biofluid. They contain different molecules that can be utilized as biomarkers, including several RNA species which they protect from degradation. Here, we present a pipeline for the development and analysis of extracellular vesicle-associated transcriptomic biomarkers that our group has successfully applied multiple times. We highlight the key steps of the pipeline and give particular emphasis to the necessary quality control checkpoints, which are linked to numerous available guidelines that should be considered along the workflow. Our pipeline starts with patient recruitment and continues with blood sampling and processing. The purification and characterization of extracellular vesicles is explained in detail, as well as the isolation and quality control of extracellular vesicle-associated RNA. We point out the possible pitfalls during library preparation and RNA sequencing and present multiple bioinformatic tools to pinpoint biomarker signature candidates from the sequencing data. Finally, considerations and pitfalls during the validation of the biomarker signature using RT-qPCR will be elaborated.

The identification of retro-DNAs in primate genomes as DNA transposons mobilizing via retrotransposition

Background

Mobile elements (MEs) constitute a major portion of the genome in primates and other higher eukaryotes, and they play important role in genome evolution and gene function. MEs can be divided into two fundamentally different classes: DNA transposons which transpose in the genome in a "cut-and-paste" style, and retrotransposons which propagate in a "copy-and-paste" fashion via a process involving transcription and reverse-transcription. In primate genomes, DNA transposons are mostly dead, while many retrotransposons are still highly active. We report here the identification of a unique group of MEs, which we call "retro-DNAs", for their combined characteristics of these two fundamentally different ME classes.

Methods

A comparative computational genomic approach was used to analyze the reference genome sequences of 10 primate species consisting of five apes, four monkeys, and marmoset.

Results

From our analysis, we identified a total of 1,750 retro-DNAs, representing 748 unique insertion events in the genomes of ten primate species including human. These retro-DNAs contain sequences of DNA transposons but lack the terminal inverted repeats (TIRs), the hallmark of DNA transposons. Instead, they show characteristics of retrotransposons, such as polyA tails, longer target-site duplications (TSDs), and the "TT/AAAA" insertion site motif, suggesting the use of the L1-based target- primed reverse transcription (TPRT) mechanism. At least 40% of these retro-DNAs locate into genic regions, presenting potentials for impacting gene function. More interestingly, some retro-DNAs, as well as their parent sites, show certain levels of expression, suggesting that they have the potential to create more retro-DNA copies in the present primate genomes.

Conclusions

Although small in number, the identification of these retro-DNAs reveals a new mean for propagating DNA transposons in primate genomes without active canonical DNA transposon activity. Our data also suggest that the TPRT machinery may transpose a wider variety of DNA sequences in the genomes.

Plasma-Free Blood as a Potential Alternative to Whole Blood for Transcriptomic Analysis

RNA sequencing (RNAseq) technology has become increasingly important in precision medicine and clinical diagnostics, and emerged as a powerful tool for identifying protein-coding genes, performing differential gene analysis, and inferring immune cell composition. Human peripheral blood samples are widely used for RNAseq, providing valuable insights into individual biomolecular information. Blood samples can be classified as whole blood (WB), plasma, serum, and remaining sediment samples, including plasma-free blood (PFB) and serum-free blood (SFB) samples that are generally considered less useful byproducts during the processes of plasma and serum separation, respectively. However, the feasibility of using PFB and SFB samples for transcriptome analysis remains unclear. In this study, we aimed to assess the suitability of employing PFB or SFB samples as an alternative RNA source in transcriptomic analysis. We performed a comparative analysis of WB, PFB, and SFB samples for different applications. Our results revealed that PFB samples exhibit greater similarity to WB samples than SFB samples in terms of protein-coding gene expression patterns, detection of differentially expressed genes, and immunological characterizations, suggesting that PFB can serve as a viable alternative to WB for transcriptomic analysis. Our study contributes to the optimization of blood sample utilization and the advancement of precision medicine research.

Supplementary Information

The online version contains supplementary material available at 10.1007/s43657-023-00121-1.

A single workflow for multi-species blood transcriptomics

BACKGROUND

Blood transcriptomic analysis is widely used to provide a detailed picture of a physiological state with potential outcomes for applications in diagnostics and monitoring of the immune response to vaccines. However, multi-species transcriptomic analysis is still a challenge from a technological point of view and a standardized workflow is urgently needed to allow interspecies comparisons.

RESULTS

Here, we propose a single and complete total RNA-Seq workflow to generate reliable transcriptomic data from blood samples from humans and from animals typically used in preclinical models. Blood samples from a maximum of six individuals and four different species (rabbit, non-human primate, mouse and human) were extracted and sequenced in triplicates. The workflow was evaluated using different wet-lab and dry-lab criteria, including RNA quality and quantity, the library molarity, the number of raw sequencing reads, the Phred-score quality, the GC content, the performance of ribosomal-RNA and globin depletion, the presence of residual DNA, the strandness, the percentage of coding genes, the number of genes expressed, and the presence of saturation plateau in rarefaction curves. We identified key criteria and their associated thresholds to be achieved for validating the transcriptomic workflow. In this study, we also generated an automated analysis of the transcriptomic data that streamlines the validation of the dataset generated.

CONCLUSIONS

Our study has developed an end-to-end workflow that should improve the standardization and the inter-species comparison in blood transcriptomics studies. In the context of vaccines and drug development, RNA sequencing data from preclinical models can be directly compared with clinical data and used to identify potential biomarkers of value to monitor safety and efficacy.

The identification of small molecule inhibitors with anthelmintic activities that target conserved proteins among ruminant gastrointestinal nematodes

Gastrointestinal nematode (GIN) infections are a major concern for the ruminant industry worldwide and result in significant production losses. Naturally occurring polyparasitism and increasing drug resistance that potentiate disease outcomes are observed among the most prevalent GINs of veterinary importance. Within the five major taxonomic clades, clade Va represents a group of GINs that predominantly affect the abomasum or small intestine of ruminants. However, the development of effective broad-spectrum anthelmintics against ruminant clade Va GINs has been challenged by a lack of comprehensive druggable genome resources. Here, we first assembled draft genomes for three clade Va species (Cooperia oncophora, Trichostrongylus colubriformis, and Ostertagia ostertagi) and compared them with closely related ruminant GINs. Genome-wide phylogenetic reconstruction showed a relationship among ruminant GINs structured by taxonomic classification. Orthogroup (OG) inference and functional enrichment analyses identified 220 clade Va-specific and Va-conserved OGs, enriched for functions related to cell cycle and cellular senescence. Further transcriptomic analysis identified 61 taxonomically and functionally conserved clade Va OGs that may function as drug targets for new broad-spectrum anthelmintics. Chemogenomic screening identified 11 compounds targeting homologs of these OGs, thus having potential anthelmintic activity. In in vitro phenotypic assays, three kinase inhibitors (digitoxigenin, K-252a, and staurosporine) exhibited broad-spectrum anthelmintic activities against clade Va GINs by obstructing the motility of exsheathed L3 (xL3) or molting of xL3 to L4. These results demonstrate valuable applications of the new ruminant GIN genomes in gaining better insights into their life cycles and offer a contemporary approach to discovering the next generation of anthelmintics.IMPORTANCEGastrointestinal nematode (GIN) infections in ruminants are caused by parasites that inhibit normal function in the digestive tract of cattle, sheep, and goats, thereby causing morbidity and mortality. Coinfection and increasing drug resistance to current therapeutic agents will continue to worsen disease outcomes and impose significant production losses on domestic livestock producers worldwide. In combination with ongoing therapeutic efforts, advancing the discovery of new drugs with novel modes of action is critical for better controlling GIN infections. The significance of this study is in assembling and characterizing new GIN genomes of Cooperia oncophora, Ostertagia ostertagi, and Trichostrongylus colubriformis for facilitating a multi-omics approach to identify novel, biologically conserved drug targets for five major GINs of veterinary importance. With this information, we were then able to demonstrate the potential of commercially available compounds as new anthelmintics.

Identification and control for the effects of bioinformatic globin depletion on human RNA-seq differential expression analysis

When profiling blood samples by RNA-sequencing (RNA-seq), RNA from haemoglobin (Hgb) can account for up to 70% of the transcriptome. Due to considerations of sequencing depth and power to detect biological variation, Hgb RNA is typically depleted prior to sequencing by hybridisation-based methods; an alternative approach is to deplete reads arising from Hgb RNA bioinformatically. In the present study, we compared the impact of these two approaches on the outcome of differential gene expression analysis performed using RNA-seq data from 58 human tuberculosis (TB) patient or contact whole blood samples-29 globin kit-depleted and 29 matched non-depleted-a subset of which were taken at TB diagnosis and at six months post-TB treatment from the same patient. Bioinformatic depletion of Hgb genes from the non-depleted samples (bioinformatic-depleted) substantially reduced library sizes (median = 57.24%) and fewer long non-coding, micro, small nuclear and small nucleolar RNAs were captured in these libraries. Profiling published TB gene signatures across all samples revealed inferior correlation between kit-depleted and bioinformatic-depleted pairs when the proportion of reads mapping to Hgb genes was higher in the non-depleted sample, particularly at the TB diagnosis time point. A set of putative "globin-fingerprint" genes were identified by directly comparing kit-depleted and bioinformatic-depleted samples at each timepoint. Two TB treatment response signatures were also shown to have decreased differential performance when comparing samples at TB diagnosis to six months post-TB treatment when profiled on the bioinformatic-depleted samples compared with their kit-depleted counterparts. These results demonstrate that failure to deplete Hgb RNA prior to sequencing has a negative impact on the sensitivity to detect disease-relevant gene expression changes even when bioinformatic removal is performed.

Transcriptomic analyses of patient peripheral blood with hemoglobin depletion reveal glioblastoma biomarkers

Peripheral blood is gaining prominence as a noninvasive alternative to tissue biopsy to develop biomarkers for glioblastoma (GBM); however, widely utilized blood-based biomarkers in clinical settings have not yet been identified due to the lack of a robust detection approach. Here, we describe the application of globin reduction in RNA sequencing of whole blood (i.e., WBGR) and perform transcriptomic analysis to identify GBM-associated transcriptomic changes. By using WBGR, we improved the detection sensitivity of informatic reads and identified differential gene expression in GBM blood. By analyzing tumor tissues, we identified transcriptomic traits of GBM blood. Further functional enrichment analyses retained the most changed genes in GBM. Subsequent validation elicited a 10-gene panel covering mRNA, long noncoding RNA, and microRNA (i.e., GBM-Dx panel) that has translational potential to aid in the early detection or clinical management of GBM. Here, we report an integrated approach, WBGR, with comprehensive analytic capacity for blood-based marker identification.

Precise reconstruction of the TME using bulk RNA-seq and a machine learning algorithm trained on artificial transcriptomes

Cellular deconvolution algorithms virtually reconstruct tissue composition by analyzing the gene expression of complex tissues. We present the decision tree machine learning algorithm, Kassandra, trained on a broad collection of >9,400 tissue and blood sorted cell RNA profiles incorporated into millions of artificial transcriptomes to accurately reconstruct the tumor microenvironment (TME). Bioinformatics correction for technical and biological variability, aberrant cancer cell expression inclusion, and accurate quantification and normalization of transcript expression increased Kassandra stability and robustness. Performance was validated on 4,000 H&E slides and 1,000 tissues by comparison with cytometric, immunohistochemical, or single-cell RNA-seq measurements. Kassandra accurately deconvolved TME elements, showing the role of these populations in tumor pathogenesis and other biological processes. Digital TME reconstruction revealed that the presence of PD-1-positive CD8⁺ T cells strongly correlated with immunotherapy response and increased the predictive potential of established biomarkers, indicating that Kassandra could potentially be utilized in future clinical applications.

Epigenomic Approaches for the Diagnosis of Rare Diseases

Rare diseases affect more than 300 million people worldwide. Diagnosing rare diseases is a major challenge as they have different causes and etiologies. Careful assessment of clinical symptoms often leads to the testing of the most common genetic alterations that could explain the disease. Patients with negative results for these tests frequently undergo whole exome or genome sequencing, leading to the identification of the molecular cause of the disease in 50% of patients at best. Therefore, a significant proportion of patients remain undiagnosed after sequencing their genome. Recently, approaches based on functional aspects of the genome, including transcriptomics and epigenomics, are beginning to emerge. Here, we will review these approaches, including studies that have successfully provided diagnoses for complex undiagnosed cases.

Is There a Brain Microbiome?

Numerous studies have identified microbial sequences or epitopes in pathological and non-pathological human brain samples. It has not been resolved if these observations are artifactual, or truly represent population of the brain by microbes. Given the tempting speculation that resident microbes could play a role in the many neuropsychiatric and neurodegenerative diseases that currently lack clear etiologies, there is a strong motivation to determine the “ground truth” of microbial existence in living brains. Here I argue that the evidence for the presence of microbes in diseased brains is quite strong, but a compelling demonstration of resident microbes in the healthy human brain remains to be done. Dedicated animal models studies may be required to determine if there is indeed a “brain microbiome.”

Application of a bioinformatic pipeline to RNA-seq data identifies novel viruslike sequence in human blood

Numerous reports have suggested that infectious agents could play a role in neurodegenerative diseases, but specific etiological agents have not been convincingly demonstrated. To search for candidate agents in an unbiased fashion, we have developed a bioinformatic pipeline that identifies microbial sequences in mammalian RNA-seq data, including sequences with no significant nucleotide similarity hits in GenBank. Effectiveness of the pipeline was tested using publicly available RNA-seq data and in a reconstruction experiment using synthetic data. We then applied this pipeline to a novel RNA-seq dataset generated from a cohort of 120 samples from amyotrophic lateral sclerosis patients and controls, and identified sequences corresponding to known bacteria and viruses, as well as novel virus-like sequences. The presence of these novel virus-like sequences, which were identified in subsets of both patients and controls, were confirmed by quantitative RT-PCR. We believe this pipeline will be a useful tool for the identification of potential etiological agents in the many RNA-seq datasets currently being generated.

Commercially Available Blocking Oligonucleotides Effectively Suppress Unwanted Hemolysis-Related miRNAs in a Large Whole-Blood RNA Cohort

When sequencing small RNA libraries derived from whole blood, the most abundant microRNAs (miRs) detected are often miR-486-5p, miR-451a, and miR-92a-3p. These highly expressed erythropoietic miRs are released into the sample from red blood cell hemolysis. Next-generation sequencing of these unwanted miRs leads to a waste in sequencing cost and diminished detection of lowly expressed miRNAs, including many potential miRNA biomarkers. Previous work has developed a method to reduce targeted miRNAs using oligonucleotides that bind their target miRNA and prevent its ligation during library construction, although the extent to which oligonucleotides can be multiplexed and their effect on larger cohorts has not been thoroughly explored. We present a method for suppressing detection of three highly abundant heme miRs in a single multiplexed blocking oligonucleotide reaction. In a small paired-sample pilot (n = 8) and a large cohort of samples (n = 901), multiplexed oligos reduced detection of their target miRNAs by approximately 70%, allowing for an approximately 10-fold increase in reads mapping to nonheme miRs and increased detection of very lowly expressed miRs, with minimal off-target effects. By removing all three highly expressed erythropoietic miRNAs from next-generational sequencing libraries, this commercially available multiplexed blocking oligonucleotide method allows for greater detection of lowly expressed biomarkers, improving the efficacy, cost-efficiency, and sensitivity of biomarker studies and diagnostic tests.

Emerging Genetic Tools to Investigate Molecular Pathways Related to Heat Stress in Chickens: A Review

Simple Summary

New genomic tools have been used as an instrument in order to assess the molecular pathway involved in heat stress resistance. Local chicken breeds have a better attitude to face heat stress. This review aims to summarize studies linked to chickens, heat stress, and heat shock protein.

Abstract

Chicken products are the most consumed animal-sourced foods at a global level across greatly diverse cultures, traditions, and religions. The consumption of chicken meat has increased rapidly in the past few decades and chicken meat is the main animal protein source in developing countries. Heat stress is one of the environmental factors which decreases the productive performance of poultry and meat quality. Heat stress produces the over-expression of heat shock factors and heat shock proteins in chicken tissues. Heat shock proteins regulate several molecular pathways in cells in response to stress conditions, changing the homeostasis of cells and tissues. These changes can affect the physiology of the tissue and hence the production ability of chickens. Indeed, commercial chicken strains can reach a high production level, but their body metabolism, being comparatively accelerated, has poor thermoregulation. In contrast, native backyard chickens are more adapted to the environments in which they live, with a robustness that allows them to survive and reproduce constantly. In the past few years, new molecular tools have been developed, such as RNA-Seq, Single Nucleotide Polymorphisms (SNPs), and bioinformatics approaches such as Genome-Wide Association Study (GWAS). Based on these genetic tools, many studies have detected the main pathways involved in cellular response mechanisms. In this context, it is necessary to clarify all the genetic and molecular mechanisms involved in heat stress response. Hence, this paper aims to review the ability of the new generation of genetic tools to clarify the molecular pathways associated with heat stress in chickens, offering new perspectives for the use of these findings in the animal breeding field.

Comparative evaluation for the globin gene depletion methods for mRNA sequencing using the whole blood-derived total RNAs

Background

There are challenges in generating mRNA-Seq data from whole-blood derived RNA as globin gene and rRNA are frequent contaminants. Given the abundance of erythrocytes in whole blood, globin genes comprise some 80% or more of the total RNA. Therefore, depletion of globin gene RNA and rRNA are critical steps required to have adequate coverage of reads mapping to the reference transcripts and thus reduce the total cost of sequencing. In this study, we directly compared the performance of probe hybridization (GLOBINClear Kit and Globin-Zero Gold rRNA Removal Kit) and RNAse-H enzymatic depletion (NEBNext® Globin & rRNA Depletion Kit and Ribo-Zero Plus rRNA Depletion Kit) methods from 1 μg of whole blood-derived RNA on mRNA-Seq profiling. All RNA samples were treated with DNaseI for additional cleanup before the depletion step and were processed for poly-A selection for library generation.

Results

Probe hybridization revealed a better overall performance than the RNAse-H enzymatic depletion method, detecting a higher number of genes and transcripts without 3′ region bias. After depletion, samples treated with probe hybridization showed globin genes at 0.5% (±0.6%) of the total mapped reads; the RNAse-H enzymatic depletion had 3.2% (±3.8%). Probe hybridization showed more junction reads and transcripts compared with RNAse-H enzymatic depletion and also had a higher correlation (R > 0.9) than RNAse-H enzymatic depletion (R > 0.85).

Conclusion

In this study, our results showed that 1 μg of high-quality RNA from whole blood could be routinely used for transcriptional profiling analysis studies with globin gene and rRNA depletion pre-processing. We also demonstrated that the probe hybridization depletion method is better suited to mRNA sequencing analysis with minimal effect on RNA quality during depletion procedures.

A Recently Formed Triploid Cardamine insueta Inherits Leaf Vivipary and Submergence Tolerance Traits of Parents

Contemporary speciation provides a unique opportunity to directly observe the traits and environmental responses of a new species. Cardamine insueta is an allotriploid species that appeared within the past 150 years in a Swiss village, Urnerboden. In contrast to its two progenitor species, Cardamine amara and Cardamine rivularis that live in wet and open habitats, respectively, C. insueta is found in-between their habitats with temporal water level fluctuation. This triploid species propagates clonally and serves as a triploid bridge to form higher ploidy species. Although niche separation is observed in field studies, the mechanisms underlying the environmental robustness of C. insueta are not clear. To characterize responses to a fluctuating environment, we performed a time-course analysis of homeolog gene expression in C. insueta in response to submergence treatment. For this purpose, the two parental (C. amara and C. rivularis) genome sequences were assembled with a reference-guided approach, and homeolog-specific gene expression was quantified using HomeoRoq software. We found that C. insueta and C. rivularis initiated vegetative propagation by forming ectopic meristems on leaves, while C. amara did not. We examined homeolog-specific gene expression of three species at nine time points during the treatment. The genome-wide expression ratio of homeolog pairs was 2:1 over the time-course, consistent with the ploidy number. By searching the genes with high coefficient of variation of expression over time-course transcriptome data, we found many known key transcriptional factors related to meristem development and formation upregulated in both C. rivularis and rivularis-homeolog of C. insueta, but not in C. amara. Moreover, some amara-homeologs of these genes were also upregulated in the triploid, suggesting trans-regulation. In turn, Gene Ontology analysis suggested that the expression pattern of submergence tolerant genes in the triploid was inherited from C. amara. These results suggest that the triploid C. insueta combined advantageous patterns of parental transcriptomes to contribute to its establishment in a new niche along a water-usage gradient.

Misuse of RPKM or TPM normalization when comparing across samples and sequencing protocols

In recent years, RNA-sequencing (RNA-seq) has emerged as a powerful technology for transcriptome profiling. For a given gene, the number of mapped reads is not only dependent on its expression level and gene length, but also the sequencing depth. To normalize these dependencies, RPKM (reads per kilobase of transcript per million reads mapped) and TPM (transcripts per million) are used to measure gene or transcript expression levels. A common misconception is that RPKM and TPM values are already normalized, and thus should be comparable across samples or RNA-seq projects. However, RPKM and TPM represent the relative abundance of a transcript among a population of sequenced transcripts, and therefore depend on the composition of the RNA population in a sample. Quite often, it is reasonable to assume that total RNA concentration and distributions are very close across compared samples. Nevertheless, the sequenced RNA repertoires may differ significantly under different experimental conditions and/or across sequencing protocols; thus, the proportion of gene expression is not directly comparable in such cases. In this review, we illustrate typical scenarios in which RPKM and TPM are misused, unintentionally, and hope to raise scientists' awareness of this issue when comparing them across samples or different sequencing protocols.

Genome-Wide DNA Methylation and Gene Expression Profiles in Cows Subjected to Different Stress Level as Assessed by Cortisol in Milk

Dairy cattle health, wellbeing and productivity are deeply affected by stress. Its influence on metabolism and immune response is well known, but the underlying epigenetic mechanisms require further investigation. In this study, we compared DNA methylation and gene expression signatures between two dairy cattle populations falling in the high- and low-variant tails of the distribution of milk cortisol concentration (MC), a neuroendocrine marker of stress in dairy cows. Reduced Representation Bisulfite Sequencing was used to obtain a methylation map from blood samples of these animals. The high and low groups exhibited similar amounts of methylated CpGs, while we found differences among non-CpG sites. Significant methylation changes were detected in 248 genes. We also identified significant fold differences in the expression of 324 genes. KEGG and Gene Ontology (GO) analysis showed that genes of both groups act together in several pathways, such as nervous system activity, immune regulatory functions and glucocorticoid metabolism. These preliminary results suggest that, in livestock, cortisol secretion could act as a trigger for epigenetic regulation and that peripheral changes in methylation can provide an insight into central nervous system functions.

Gene Expression: the Key to Understanding HIV-1 Infection?

Gene expression profiling of the host response to HIV infection has promised to fill the gaps in our knowledge and provide new insights toward vaccine and cure. However, despite 20 years of research, the biggest questions remained unanswered. A literature review identified 62 studies examining gene expression dysregulation in samples from individuals living with HIV. Changes in gene expression were dependent on cell/tissue type, stage of infection, viremia, and treatment status. Some cell types, notably CD4+ T cells, exhibit upregulation of cell cycle, interferon-related, and apoptosis genes consistent with depletion. Others, including CD8+ T cells and natural killer cells, exhibit perturbed function in the absence of direct infection with HIV. Dysregulation is greatest during acute infection. Differences in study design and data reporting limit comparability of existing research and do not as yet provide a coherent overview of gene expression in HIV. This review outlines the extraordinarily complex host response to HIV and offers recommendations to realize the full potential of HIV host transcriptomics.

Effects of Cardiac Sympathetic Neurodegeneration and PPARγ Activation on Rhesus Macaque Whole Blood miRNA and mRNA Expression Profiles

Degeneration of sympathetic innervation of the heart occurs in numerous diseases, including diabetes, idiopathic REM sleep disorder, and Parkinson's disease (PD). In PD, cardiac sympathetic denervation occurs in 80-90% of patients and can begin before the onset of motor symptoms. Today, there are no disease-modifying therapies for cardiac sympathetic neurodegeneration, and biomarkers are limited to radioimaging techniques. Analysis of expression levels of coding mRNA and noncoding RNAs, such as microRNAs (miRNAs), can uncover pathways involved in disease, leading to the discovery of biomarkers, pathological mechanisms, and potential drug targets. Whole blood in particular is a clinically relevant source of biomarkers, as blood sampling is inexpensive and simple to perform. Our research group has previously developed a nonhuman primate model of cardiac sympathetic denervation by intravenous administration of the catecholaminergic neurotoxin 6-hydroxydopamine (6-OHDA). In this rhesus macaque (Macaca mulatta) model, imaging with positron emission tomography showed that oral administration of the peroxisome proliferator-activated receptor gamma (PPARγ) agonist pioglitazone (n = 5; 5 mg/kg daily) significantly decreased cardiac inflammation and oxidative stress compared to placebo (n = 5). Here, we report our analysis of miRNA and mRNA expression levels over time in the whole blood of these monkeys. Differential expression of three miRNAs was induced by 6-OHDA (mml-miR-16-2-3p, mml-miR-133d-3p, and mml-miR-1262-5p) and two miRNAs by pioglitazone (mml-miR-204-5p and mml-miR-146b-5p) at 12 weeks posttoxin, while expression of mRNAs involved in inflammatory cytokines and receptors was not significantly affected. Overall, this study contributes to the characterization of rhesus coding and noncoding RNA profiles in normal and disease-like conditions, which may facilitate the identification and clinical translation of biomarkers of cardiac neurodegeneration and neuroprotection.

RNA-Seq of human whole blood: Evaluation of globin RNA depletion on Ribo-Zero library method

Peripheral blood is a highly accessible biofluid providing a rich source of information about human physiology and health status. However, for studies of the blood transcriptome with RNA sequencing (RNA-Seq) techniques, high levels of hemoglobin mRNAs (hgbRNA) present in blood can occupy valuable sequencing space, impacting detection and quantification of non-hgbRNAs. In this study, we evaluated two methods for preparing ribosomal RNA (rRNA)-depleted sequencing libraries for RNA-Seq of whole blood, one of which is also designed to deplete hgbRNAs. Two experiments were performed: one evaluating library performance across 6 human blood samples and the other examining library reproducibility and performance in a two-subject subset. We find that addition of hgbRNA depletion to the rRNA-depletion protocol for library preparation from blood RNA effectively reduces highly abundant hgbRNA reads; however, it does not result in a statistically significant increase in differentially expressed genes in our patient-control study. Bioinformatic removal of globin gene counts in non-hgbRNA depleted libraries provides improvement in overall performance of these libraries. We conclude that use of a standard ribosomal RNA depletion method for library preparation coupled with bioinformatic removal of globin gene counts is sufficient for reproducible and sensitive measurement of both coding and noncoding RNAs in the blood transcriptome.

Evaluation of Transcriptomic Regulations behind Metabolic Syndrome in Obese and Lean Subjects

Multiple mechanisms have been suggested to confer to the pathophysiology of metabolic syndrome (MetS), however despite great interest from the scientific community, the exact contribution of each of MetS risk factors still remains unclear. The present study aimed to investigate molecular signatures in peripheral blood of individuals affected by MetS and different degrees of obesity. Metabolic health of 1204 individuals from 1000PLUS cohort was assessed, and 32 subjects were recruited to four study groups: MetS lean, MetS obese, “healthy obese”, and healthy lean. Whole-blood transcriptome next generation sequencing with functional data analysis were carried out. MetS obese and MetS lean study participants showed the upregulation of genes involved in inflammation and coagulation processes: granulocyte adhesion and diapedesis (p < 0.0001, p = 0.0063), prothrombin activation pathway (p = 0.0032, p = 0.0091), coagulation system (p = 0.0010, p = 0.0155). The results for “healthy obese” indicate enrichment in molecules associated with protein synthesis (p < 0.0001), mitochondrial dysfunction (p < 0.0001), and oxidative phosphorylation (p < 0.0001). Our results suggest that MetS is related to the state of inflammation and vascular system changes independent of excess body weight. Furthermore, “healthy obese”, despite not fulfilling the criteria for MetS diagnosis, seems to display an intermediate state with a lower degree of metabolic abnormalities, before they proceed to a full blown MetS.

Depletion of erythropoietic miR-486-5p and miR-451a improves detectability of rare microRNAs in peripheral blood-derived small RNA sequencing libraries

Erythroid-specific miR-451a and miR-486-5p are two of the most dominant microRNAs (miRNAs) in human peripheral blood. In small RNA sequencing libraries, their overabundance reduces diversity as well as complexity and consequently causes negative effects such as missing detectability and inaccurate quantification of low abundant miRNAs. Here we present a simple, cost-effective and easy to implement hybridization-based method to deplete these two erythropoietic miRNAs from blood-derived RNA samples. By utilization of blocking oligonucleotides, this method provides a highly efficient and specific depletion of miR-486-5p and miR-451a, which leads to a considerable increase of measured expression as well as detectability of low abundant miRNA species. The blocking oligos are compatible with common 5′ ligation-dependent small RNA library preparation protocols, including commercially available kits, such as Illumina TruSeq and Perkin Elmer NEXTflex. Furthermore, the here described method and oligo design principle can be easily adapted to target many other miRNA molecules, depending on context and research question.

Prospective Molecular Profiling of Circulating Tumor Cells from Patients with Melanoma Receiving Combinatorial Immunotherapy

BACKGROUND

Blood molecular profiling of circulating tumor cells (CTCs) can enable monitoring of patients with metastatic melanoma during checkpoint inhibitor immunotherapy (CII) and in combination with targeted therapies. We developed a microfluidics-based CTC platform to explore CTC profiling utility in CII-treated patients with melanoma using a melanoma messenger RNA (mRNA)/DNA biomarker panel.

METHODS

Blood samples (n = 213) were collected prospectively from 75 American Joint Committee on Cancer-staged III/IV melanoma patients during CII treatment and those enriched for CTCs. CTC profiling was performed using 5 known melanoma mRNA biomarkers and BRAF V600E DNA mutation. CTC biomarker status associations with clinical outcomes were assessed.

RESULTS

CTCs were detected in 88% of blood samples from patients with melanoma. CTC-derived biomarkers and clinical variables analyzed using classification and regression tree analysis revealed that a combination of lactate dehydrogenase, CTC-mRNA biomarkers, and tumor BRAF-mutation status was indicative of clinical outcomes for patients with stage IV melanoma (n = 52). The panel stratified low-risk and high-risk patients, whereby the latter had poor disease-free (P = 0.03) and overall survival (P = 0.02). Incorporation of a DNA biomarker with mRNA profiling increased overall CTC-detection capability by 57% compared to mRNA profiling only. RNA sequencing of isolated CTCs identified significant catenin beta 1 (CTNNB1) overexpression (P <0.01) compared to nondisease donor blood. CTC-CTNNB1 was associated with progressive disease/stable disease compared to complete-responder patient status (P = 0.02). Serial CTC profiling identified subclinical disease in patients who developed progressive disease during treatment/follow-up.

CONCLUSIONS

CTC-derived mRNA/DNA biomarkers have utility for monitoring CII, targeted, and combinatorial therapies in metastatic melanoma patients.

Effectiveness of integrated interpretation of exome and corresponding transcriptome data for detecting splicing variants of genes associated with autosomal recessive disorders

Purpose

Part of the weakness of exome analysis lies in the inability to detect aberrant splicing. An evaluation of the post-splicing mRNA sequence concurrently with genomic variants could improve the diagnostic rate. We aimed to investigate publicly available exome sequencing data and its matching transcriptomics data of phenotypically normal individuals to identify alternatively spliced variants from known genes associated with autosomal recessive disorders under the premise that some of the subjects could be carriers of such disorders.

Methods

Aberrant splicing events and their triggering genomic variants were detected with the aid of Bayesian network method “SAVNet” which was originally developed for cancer genomics.

Results

Forty aberrant splicing events including exon skipping, the creation of a new splice site, and the use of a cryptic splice site in response to the disruption of the authentic site were detected in 1916 genes among 31 of the 179 subjects from the 1000 Genomes Project. The predicted effects on proteins were either frameshift mutations (30) or large in-frame insertions or deletions (10). Five missense mutations and 2 silent mutations were reinterpreted as triggering major changes in transcript sequences. The detection rate of provisionally truncating pathogenic variants increased by 19%, compared with a conventional exome analysis.

Conclusion

The coupling interpretation of exome and transcriptome data enhances the performance of conventional exome analyses through the proper interpretation of intronic variants that are outside of the GT/AG splicing consensus sequences and also allows the reinterpretation of “missense” or “silent” substitutions that can indeed have drastic effects on splicing.

The effects of a globin blocker on the resolution of 3'mRNA sequencing data in porcine blood

Background

Gene expression profiling in blood is a potential source of biomarkers to evaluate or predict phenotypic differences between pigs but is expensive and inefficient because of the high abundance of globin mRNA in porcine blood. These limitations can be overcome by the use of QuantSeq 3’mRNA sequencing (QuantSeq) combined with a method to deplete or block the processing of globin mRNA prior to or during library construction. Here, we validated the effectiveness of QuantSeq using a novel specific globin blocker (GB) that is included in the library preparation step of QuantSeq.

Results

In data set 1, four concentrations of the GB were applied to RNA samples from two pigs. The GB significantly reduced the proportion of globin reads compared to non-GB (NGB) samples (P = 0.005) and increased the number of detectable non-globin genes. The highest evaluated concentration (C1) of the GB resulted in the largest reduction of globin reads compared to the NGB (from 56.4 to 10.1%). The second highest concentration C2, which showed very similar globin depletion rates (12%) as C1 but a better correlation of the expression of non-globin genes between NGB and GB (r = 0.98), allowed the expression of an additional 1295 non-globin genes to be detected, although 40 genes that were detected in the NGB sample (at a low level) were not present in the GB library. Concentration C2 was applied in the rest of the study. In data set 2, the distribution of the percentage of globin reads for NGB (n = 184) and GB (n = 189) samples clearly showed the effects of the GB on reducing globin reads, in particular for HBB, similar to results from data set 1. Data set 3 (n = 84) revealed that the proportion of globin reads that remained in GB samples was significantly and positively correlated with the reticulocyte count in the original blood sample (P < 0.001).

Conclusions

The effect of the GB on reducing the proportion of globin reads in porcine blood QuantSeq was demonstrated in three data sets. In addition to increasing the efficiency of sequencing non-globin mRNA, the GB for QuantSeq has an advantage that it does not require an additional step prior to or during library creation. Therefore, the GB is a useful tool in the quantification of whole gene expression profiles in porcine blood.

The national blueprint for pregnancy/birth longitudinal cohorts to study factor VIII immunogenicity: NHLBI State of the Science (SOS) Workshop on factor VIII inhibitors

INTRODUCTION

Patients with haemophilia can develop inhibitors to exogenous coagulation factors. Some patients are tolerant to factor, while those who develop inhibitors do so early in life. Genetics and environmental factors are known to contribute to inhibitor risk. However, it is not yet possible to predict inhibitor formation or treatment responsiveness in individuals. We hypothesize that factors in the antenatal/neonatal period inform inhibitor risk development.

AIM

To consider the design of longitudinal studies beginning in the antenatal/neonatal period and the use of new technologies to better understand haemophilia inhibitors.

METHODS

A working group was formed for the NHLBI State of the Science Workshop: Factor VIII Inhibitors: Generating a National Blueprint for Future Research to solicit input from the US haemophilia community and international collaborators to consider design of pregnancy/birth longitudinal cohorts that leverage -omics, existing phenotypic data, and in silico modelling to study inhibitors.

RESULTS

An antenatal/neonatal longitudinal cohort should begin with enrolment of pregnant genetic carriers of haemophilia and span the at-risk period for inhibitor development in the child. Data and samples from the mother, placenta, neonate and young child can be obtained that are amenable to existing assays, genomics and other -omics studies. Data can inform in silico prediction and mathematical models.

CONCLUSION

A longitudinal study beginning before birth offers the unique opportunity to study factors that influence inhibitor development prior to exposure. Advances in -omics and computational biology can study complex phenotypes in this rare disease. This study could be accomplished through interdisciplinary efforts and patient community engagement.

Depletion of Hemoglobin Transcripts and Long-Read Sequencing Improves the Transcriptome Annotation of the Polar Bear (Ursus maritimus)

Transcriptome studies evaluating whole blood and tissues are often confounded by overrepresentation of highly abundant transcripts. These abundant transcripts are problematic, as they compete with and prevent the detection of rare RNA transcripts, obscuring their biological importance. This issue is more pronounced when using long-read sequencing technologies for isoform-level transcriptome analysis, as they have relatively lower throughput compared to short-read sequencers. As a result, long-read based transcriptome analysis is prohibitively expensive for non-model organisms. While there are off-the-shelf kits available for select model organisms capable of depleting highly abundant transcripts for alpha (HBA) and beta (HBB) hemoglobin, they are unsuitable for non-model organisms. To address this, we have adapted the recent CRISPR/Cas9-based depletion method (depletion of abundant sequences by hybridization) for long-read full-length cDNA sequencing approaches that we call Long-DASH. Using a recombinant Cas9 protein with appropriate guide RNAs, full-length hemoglobin transcripts can be depleted in vitro prior to performing any short- and long-read sequencing library preparations. Using this method, we sequenced depleted full-length cDNA in parallel using both our Oxford Nanopore Technology (ONT) based R2C2 long-read approach, as well as the Illumina short-read based Smart-seq2 approach. To showcase this, we have applied our methods to create an isoform-level transcriptome from whole blood samples derived from three polar bears (Ursus maritimus). Using Long-DASH, we succeeded in depleting hemoglobin transcripts and generated deep Smart-seq2 Illumina datasets and 3.8 million R2C2 full-length cDNA consensus reads. Applying Long-DASH with our isoform identification pipeline, Mandalorion, we discovered ∼6,000 high-confidence isoforms and a number of novel genes. This indicates that there is a high diversity of gene isoforms within U. maritimus not yet reported. This reproducible and straightforward approach has not only improved the polar bear transcriptome annotations but will serve as the foundation for future efforts to investigate transcriptional dynamics within the 19 polar bear subpopulations around the Arctic.

Multi-year whole-blood transcriptome data for the study of onset and progression of Parkinson's Disease

Parkinson’s disease (PD) is an age-related, chronic and progressive neurodegenerative disorder characterized by a loss of multifocal neurons, resulting in both non-motor and motor symptoms. While several genetic and environmental contributory risk factors have been identified, more exact methods for diagnosing and assessing prognosis of PD have yet to be established. Here we describe the generation and validation of a dataset comprising whole-blood transcriptomes originally intended for use in detection of blood biomarkers and transcriptomic network changes indicative of PD. Whole-blood samples extracted from both early-stage PD patients and healthy controls were sequenced using no-amplification non-tagging cap analysis of gene expression (nAnT-iCAGE) to analyse differences in global RNA expression patterns across the conditions. Subsequent sampling of a subset of PD patients one-year later provides the opportunity to study changes in transcriptomes arising due to disease progression.

Design Type(s)	disease state design • transcription profiling design • parallel group design
Measurement Type(s)	transcription profiling assay
Technology Type(s)	RNA sequencing
Factor Type(s)	age • duration of disease • biological sex • disease severity measurement • experimental condition
Sample Characteristic(s)	Homo sapiens • blood

Machine-accessible metadata file describing the reported data (ISA-Tab format)

A gene regulatory architecture that controls region-independent dynamics of oligodendrocyte differentiation

Oligodendrocytes (OLs) facilitate information processing in the vertebrate central nervous system via axonal ensheathment. The structure and dynamics of the regulatory network that mediates oligodendrogenesis are poorly understood. We employed bioinformatics and meta-analysis of high-throughput datasets to reconstruct a regulatory network underpinning OL differentiation. From this network, we identified families of feedforward loops comprising the transcription factors (TFs) Olig2, Sox10, and Tcf7l2 and their targets. Among the targets, we found eight other TFs related to OL differentiation, suggesting a hierarchical architecture in which some TFs (Olig2, Sox10, and Tcf7l2) regulate via feedforward loops the expression of others (Sox2, Sox6, Sox11, Nkx2-2, Nkx6-2, Hes5, Myt1, and Myrf). Model simulations with a kinetic model reproduced the mechanisms of OL differentiation only when in the model, Sox10-mediated repression of Tcf7l2 by miR-338/miR-155 was introduced, a prediction confirmed in genetic functional experiments. Additional model simulations suggested that OLs from dorsal regions emerge through BMP/Sox9 signaling.

RNA Sequencing (RNA-Seq) Reveals Extremely Low Levels of Reticulocyte-Derived Globin Gene Transcripts in Peripheral Blood From Horses (Equus caballus) and Cattle (Bos taurus)

RNA-seq has emerged as an important technology for measuring gene expression in peripheral blood samples collected from humans and other vertebrate species. In particular, transcriptomics analyses of whole blood can be used to study immunobiology and develop novel biomarkers of infectious disease. However, an obstacle to these methods in many mammalian species is the presence of reticulocyte-derived globin mRNAs in large quantities, which can complicate RNA-seq library sequencing and impede detection of other mRNA transcripts. A range of supplementary procedures for targeted depletion of globin transcripts have, therefore, been developed to alleviate this problem. Here, we use comparative analyses of RNA-seq data sets generated from human, porcine, equine, and bovine peripheral blood to systematically assess the impact of globin mRNA on routine transcriptome profiling of whole blood in cattle and horses. The results of these analyses demonstrate that total RNA isolated from equine and bovine peripheral blood contains very low levels of globin mRNA transcripts, thereby negating the need for globin depletion and greatly simplifying blood-based transcriptomic studies in these two domestic species.

Transcriptome display during tilapia sex determination and differentiation as revealed by RNA-Seq analysis

Background

The factors determining sex in teleosts are diverse. Great efforts have been made to characterize the underlying genetic network in various species. However, only seven master sex-determining genes have been identified in teleosts. While the function of a few genes involved in sex determination and differentiation has been studied, we are far from fully understanding how genes interact to coordinate in this process.

Results

To enable systematic insights into fish sexual differentiation, we generated a dynamic co-expression network from tilapia gonadal transcriptomes at 5, 20, 30, 40, 90, and 180 dah (days after hatching), plus 45 and 90 dat (days after treatment) and linked gene expression profiles to both development and sexual differentiation. Transcriptomic profiles of female and male gonads at 5 and 20 dah exhibited high similarities except for a small number of genes that were involved in sex determination, while drastic changes were observed from 90 to 180 dah, with a group of differently expressed genes which were involved in gonadal differentiation and gametogenesis. Weighted gene correlation network analysis identified changes in the expression of Borealin, Gtsf1, tesk1, Zar1, Cdn15, and Rpl that were correlated with the expression of genes previously known to be involved in sex differentiation, such as Foxl2, Cyp19a1a, Gsdf, Dmrt1, and Amh.

Conclusions

Global gonadal gene expression kinetics during sex determination and differentiation have been extensively profiled in tilapia. These findings provide insights into the genetic framework underlying sex determination and sexual differentiation, and expand our current understanding of developmental pathways during teleost sex determination.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4756-0) contains supplementary material, which is available to authorized users.

A Bloody Primer: Analysis of RNA-Seq from Tissue Admixtures

RNA sequencing is a powerful technology that allows for unbiased profiling of the entire transcriptome. The analysis of transcriptome profiles from heterogeneous tissues, cell admixtures with relative proportions that can vary several fold across samples, poses a significant challenge. Blood is perhaps the most egregious example. Here, we describe in detail a computational pipeline for RNA-Seq data preparation and statistical analysis, with development of a means of estimating the cell type composition of blood samples from their bulk RNA-Seq profiles. We also illustrate the importance of adjusting for the potential confounding effect of cellular heterogeneity in the context of statistical inference in a whole blood RNA-Seq dataset.

Talking the talk, but not walking the walk: RT-qPCR as a paradigm for the lack of reproducibility in molecular research

Poorly executed and inadequately reported molecular measurement methods are amongst the causes underlying the lack of reproducibility of much biomedical research. Although several high impact factor journals have acknowledged their past failure to scrutinise adequately the technical soundness of manuscripts, there is a perplexing reluctance to implement basic corrective measures. The reverse transcription real-time quantitative PCR (RT-qPCR) is probably the most straightforward measurement technique available for RNA quantification and is widely used in research, diagnostic, forensic and biotechnology applications. Despite the impact of the minimum information for the publication of quantitative PCR experiments (MIQE) guidelines, which aim to improve the robustness and the transparency of reporting of RT-qPCR data, we demonstrate that elementary protocol errors, inappropriate data analysis and inadequate reporting continue to be rife and conclude that the majority of published RT-qPCR data are likely to represent technical noise.

Caloric restriction delays age-related methylation drift

In mammals, caloric restriction consistently results in extended lifespan. Epigenetic information encoded by DNA methylation is tightly regulated, but shows a striking drift associated with age that includes both gains and losses of DNA methylation at various sites. Here, we report that epigenetic drift is conserved across species and the rate of drift correlates with lifespan when comparing mice, rhesus monkeys, and humans. Twenty-two to 30-year-old rhesus monkeys exposed to 30% caloric restriction since 7–14 years of age showed attenuation of age-related methylation drift compared to ad libitum-fed controls such that their blood methylation age appeared 7 years younger than their chronologic age. Even more pronounced effects were seen in 2.7–3.2-year-old mice exposed to 40% caloric restriction starting at 0.3 years of age. The effects of caloric restriction on DNA methylation were detectable across different tissues and correlated with gene expression. We propose that epigenetic drift is a determinant of lifespan in mammals.

Caloric restriction has been shown to increase lifespan in mammals. Here, the authors provide evidence that age-related methylation drift correlates with lifespan and that caloric restriction in mice and rhesus monkeys results in attenuation of age-related methylation drift.

Deep Sequencing of RNA from Blood and Oral Swab Samples Reveals the Presence of Nucleic Acid from a Number of Pathogens in Patients with Acute Ebola Virus Disease and Is Consistent with Bacterial Translocation across the Gut

In this study, samples from the 2013-2016 West African Ebola virus outbreak from patients in Guinea with Ebola virus disease (EVD) were analyzed to discover and classify what other pathogens were present. Throat swabs were taken from deceased EVD patients, and peripheral blood samples were analyzed that had been taken from patients when they presented at the treatment center with acute illness. High-throughput RNA sequencing (RNA-seq) and bioinformatics were used to identify the potential microorganisms. This approach confirmed Ebola virus (EBOV) in all samples from patients diagnosed as acute positive for the virus by quantitative reverse transcription-PCR in deployed field laboratories. Nucleic acid mapping to Plasmodium was also used on the patient samples, confirming results obtained with an antigen-based rapid diagnostic test (RDT) conducted in the field laboratories. The data suggested that a high Plasmodium load, as determined by sequence read depth, was associated with mortality and influenced the host response, whereas a lower parasite load did not appear to affect outcome. The identifications of selected bacteria from throat swabs via RNA-seq were confirmed by culture. The data indicated that the potential pathogens identified in the blood samples were associated with translocation from the gut, suggesting the presence of bacteremia, which transcriptome data suggested may induce or aggravate the acute-phase response observed during EVD. Transcripts mapping to different viruses were also identified, including those indicative of lytic infections. The development of high-resolution analysis of samples from patients with EVD will help inform care pathways and the most appropriate general antimicrobial therapy to be used in a resource-poor setting. IMPORTANCE Our results highlight the identification of an array of pathogens in the blood of patients with Ebola virus disease (EVD). This has not been done before, and the data have important implications for the treatment of patients with EVD, particularly considering antibiotic stewardship. We show that EVD patients who were also infected with Plasmodium, particularly at higher loads, had more adverse outcomes than patients with lower levels of Plasmodium. However, the presence of Plasmodium did not influence the innate immune response, and it is likely that the presence of EBOV dominated this response. Several viruses other than EBOV were identified, and bacteria associated with sepsis were also identified. These findings were indicative of bacterial translocation across the gut during the acute phase of EVD.

RNA-seq mixology: designing realistic control experiments to compare protocols and analysis methods

Carefully designed control experiments provide a gold standard for benchmarking different genomics research tools. A shortcoming of many gene expression control studies is that replication involves profiling the same reference RNA sample multiple times. This leads to low, pure technical noise that is atypical of regular studies. To achieve a more realistic noise structure, we generated a RNA-sequencing mixture experiment using two cell lines of the same cancer type. Variability was added by extracting RNA from independent cell cultures and degrading particular samples. The systematic gene expression changes induced by this design allowed benchmarking of different library preparation kits (standard poly-A versus total RNA with Ribozero depletion) and analysis pipelines. Data generated using the total RNA kit had more signal for introns and various RNA classes (ncRNA, snRNA, snoRNA) and less variability after degradation. For differential expression analysis, voom with quality weights marginally outperformed other popular methods, while for differential splicing, DEXSeq was simultaneously the most sensitive and the most inconsistent method. For sample deconvolution analysis, DeMix outperformed IsoPure convincingly. Our RNA-sequencing data set provides a valuable resource for benchmarking different protocols and data pre-processing workflows. The extra noise mimics routine lab experiments more closely, ensuring any conclusions are widely applicable.

A comprehensive assessment of RNA-seq protocols for degraded and low-quantity samples

BACKGROUND

RNA-sequencing (RNA-seq) has emerged as one of the most sensitive tool for gene expression analysis. Among the library preparation methods available, the standard poly(A) + enrichment provides a comprehensive, detailed, and accurate view of polyadenylated RNAs. However, on samples of suboptimal quality ribosomal RNA depletion and exon capture methods have recently been reported as better alternatives.

METHODS

We compared for the first time three commercial Illumina library preparation kits (TruSeq Stranded mRNA, TruSeq Ribo-Zero rRNA Removal, and TruSeq RNA Access) as representatives of these three different approaches using well-established human reference RNA samples from the MAQC/SEQC consortium on a wide range of input amounts (from 100 ng down to 1 ng) and degradation levels (intact, degraded, and highly degraded).

RESULTS

We assessed the accuracy of the generated expression values by comparison to gold standard TaqMan qPCR measurements and gained unprecedented insight into the limits of applicability in terms of input quantity and sample quality of each protocol. We found that each protocol generates highly reproducible results (R ² > 0.92) on intact RNA samples down to input amounts of 10 ng. For degraded RNA samples, Ribo-Zero showed clear performance advantages over the other two protocols as it generated more accurate and better reproducible gene expression results even at very low input amounts such as 1 ng and 2 ng. For highly degraded RNA samples, RNA Access performed best generating reliable data down to 5 ng input.

CONCLUSIONS

We found that the ribosomal RNA depletion protocol from Illumina works very well at amounts far below recommendation and over a good range of intact and degraded material. We also infer that the exome-capture protocol (RNA Access, Illumina) performs better than other methods on highly degraded and low amount samples.

Transcriptome analysis illuminates the nature of the intracellular interaction in a vertebrate-algal symbiosis

During embryonic development, cells of the green alga Oophila amblystomatis enter cells of the salamander Ambystoma maculatum forming an endosymbiosis. Here, using de novo dual-RNA seq, we compared the host salamander cells that harbored intracellular algae to those without algae and the algae inside the animal cells to those in the egg capsule. This two-by-two-way analysis revealed that intracellular algae exhibit hallmarks of cellular stress and undergo a striking metabolic shift from oxidative metabolism to fermentation. Culturing experiments with the alga showed that host glutamine may be utilized by the algal endosymbiont as a primary nitrogen source. Transcriptional changes in salamander cells suggest an innate immune response to the alga, with potential attenuation of NF-κB, and metabolic alterations indicative of modulation of insulin sensitivity. In stark contrast to its algal endosymbiont, the salamander cells did not exhibit major stress responses, suggesting that the host cell experience is neutral or beneficial.

PINTnet: construction of condition-specific pathway interaction network by computing shortest paths on weighted PPI

Background

Identifying perturbed pathways in a given condition is crucial in understanding biological phenomena. In addition to identifying perturbed pathways individually, pathway analysis should consider interactions among pathways. Currently available pathway interaction prediction methods are based on the existence of overlapping genes between pathways, protein-protein interaction (PPI) or functional similarities. However, these approaches just consider the pathways as a set of genes, thus they do not take account of topological features. In addition, most of the existing approaches do not handle the explicit gene expression quantity information that is routinely measured by RNA-sequecing.

Results

To overcome these technical issues, we developed a new pathway interaction network construction method using PPI, closeness centrality and shortest paths. We tested our approach on three different high-throughput RNA-seq data sets: pregnant mice data to reveal the role of serotonin on beta cell mass, bone-metastatic breast cancer data and autoimmune thyroiditis data to study the role of IFN- α. Our approach successfully identified the pathways reported in the original papers. For the pathways that are not directly mentioned in the original papers, we were able to find evidences of pathway interactions by the literature search. Our method outperformed two existing approaches, overlapping gene-based approach (OGB) and protein-protein interaction-based approach (PB), in experiments with the three data sets.

Conclusion

Our results show that PINTnet successfully identified condition-specific perturbed pathways and the interactions between the pathways. We believe that our method will be very useful in characterizing biological mechanisms at the pathway level. PINTnet is available at http://biohealth.snu.ac.kr/software/PINTnet/.

Breed and adaptive response modulate bovine peripheral blood cells' transcriptome

BACKGROUND

Adaptive response includes a variety of physiological modifications to face changes in external or internal conditions and adapt to a new situation. The acute phase proteins (APPs) are reactants synthesized against environmental stimuli like stress, infection, inflammation.

METHODS

To delineate the differences in molecular constituents of adaptive response to the environment we performed the whole-blood transcriptome analysis in Italian Holstein (IH) and Italian Simmental (IS) breeds. For this, 663 IH and IS cows from six commercial farms were clustered according to the blood level of APPs. Ten extreme individuals (five APP+ and APP- variants) from each farm were selected for the RNA-seq using the Illumina sequencing technology. Differentially expressed (DE) genes were analyzed using dynamic impact approach (DIA) and DAVID annotation clustering. Milk production data were statistically elaborated to assess the association of APP+ and APP- gene expression patterns with variations in milk parameters.

RESULTS

The overall de novo assembly of cDNA sequence data generated 13,665 genes expressed in bovine blood cells. Comparative genomic analysis revealed 1,152 DE genes in the comparison of all APP+ vs. all APP- variants; 531 and 217 DE genes specific for IH and IS comparison respectively. In all comparisons overexpressed genes were more represented than underexpressed ones. DAVID analysis revealed 369 DE genes across breeds, 173 and 73 DE genes in IH and IS comparison respectively. Among the most impacted pathways for both breeds were vitamin B6 metabolism, folate biosynthesis, nitrogen metabolism and linoleic acid metabolism.

CONCLUSIONS

Both DIA and DAVID approaches produced a high number of significantly impacted genes and pathways with a narrow connection to adaptive response in cows with high level of blood APPs. A similar variation in gene expression and impacted pathways between APP+ and APP- variants was found between two studied breeds. Such similarity was also confirmed by annotation clustering of the DE genes. However, IH breed showed higher and more differentiated impacts compared to IS breed and such particular features in the IH adaptive response could be explained by its higher metabolic activity. Variations of milk production data were significantly associated with APP+ and APP- gene expression patterns.

Transcriptomic signatures differentiate survival from fatal outcomes in humans infected with Ebola virus

Background

In 2014, Western Africa experienced an unanticipated explosion of Ebola virus infections. What distinguishes fatal from non-fatal outcomes remains largely unknown, yet is key to optimising personalised treatment strategies. We used transcriptome data for peripheral blood taken from infected and convalescent recovering patients to identify early stage host factors that are associated with acute illness and those that differentiate patient survival from fatality.

Results

The data demonstrate that individuals who succumbed to the disease show stronger upregulation of interferon signalling and acute phase responses compared to survivors during the acute phase of infection. Particularly notable is the strong upregulation of albumin and fibrinogen genes, which suggest significant liver pathology. Cell subtype prediction using messenger RNA expression patterns indicated that NK-cell populations increase in patients who survive infection. By selecting genes whose expression properties discriminated between fatal cases and survivors, we identify a small panel of responding genes that act as strong predictors of patient outcome, independent of viral load.

Conclusions

Transcriptomic analysis of the host response to pathogen infection using blood samples taken during an outbreak situation can provide multiple levels of information on both disease state and mechanisms of pathogenesis. Host biomarkers were identified that provide high predictive value under conditions where other predictors, such as viral load, are poor prognostic indicators. The data suggested that rapid analysis of the host response to infection in an outbreak situation can provide valuable information to guide an understanding of disease outcome and mechanisms of disease.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-016-1137-3) contains supplementary material, which is available to authorized users.

RNA sequencing of archived neonatal dried blood spots

Neonatal dried blood spots (DBS) are routinely collected on standard Guthrie cards for all-comprising national newborn screening programs for inborn errors of metabolism, hypothyroidism and other diseases. In Denmark, the Guthrie cards are stored at − 20 °C in the Danish Neonatal Screening Biobank and each sample is linked to elaborate social and medical registries. This provides a unique biospecimen repository to enable large population research at a perinatal level. Here, we demonstrate the feasibility to obtain gene expression data from DBS using next-generation RNA sequencing (RNA-seq). RNA-seq was performed on five males and five females. Sequencing results have an average of > 30 million reads per sample. 26,799 annotated features can be identified with 64% features detectable without fragments per kilobase of transcript per million mapped reads (FPKM) cutoff; number of detectable features dropped to 18% when FPKM ≥ 1. Sex can be discriminated using blood-based sex-specific gene set identified by the Genotype-Tissue Expression consortium. Here, we demonstrate the feasibility to acquire biologically-relevant gene expression from DBS using RNA-seq which provide a new avenue to investigate perinatal diseases in a high throughput manner.

RNA-Seq analysis of seasonal and individual variation in blood transcriptomes of healthy managed bottlenose dolphins

Background

The blood transcriptome can reflect both systemic exposures and pathological changes in other organs of the body because immune cells recirculate through the blood, lymphoid tissues, and affected sites. In human and veterinary medicine, blood transcriptome analysis has been used successfully to identify markers of disease or pathological conditions, but can be confounded by large seasonal changes in expression. In comparison, the use of transcriptomic based analyses in wildlife has been limited. Here we report a longitudinal study of four managed bottlenose dolphins located in Waikoloa, Hawaii, serially sampled (approximately monthly) over the course of 1 year to establish baseline information on the content and variation of the dolphin blood transcriptome.

Results

Illumina based RNA-seq analyses were carried out using both the Ensembl dolphin genome and a de novo blood transcriptome as guides. Overall, the blood transcriptome encompassed a wide array of cellular functions and processes and was relatively stable within and between animals over the course of 1 year. Principal components analysis revealed moderate clustering by sex associated with the variation among global gene expression profiles (PC1, 22 % of variance). Limited seasonal change was observed, with < 2.5 % of genes differentially expressed between winter and summer months (FDR < 0.05). Among the differentially expressed genes, cosinor analysis identified seasonal rhythmicity for the observed changes in blood gene expression, consistent with studies in humans. While the proportion of seasonally variant genes in these dolphins is much smaller than that reported in humans, the majority of those identified in dolphins were also shown to vary with season in humans. Gene co-expression network analysis identified several gene modules with significant correlation to age, sex, or hematological parameters.

Conclusions

This longitudinal analysis of healthy managed dolphins establishes a preliminary baseline for blood transcriptome analysis in this species. Correlations with hematological parameters, distinct from muted seasonal effects, suggest that the otherwise relatively stable blood transcriptome may be a useful indicator of health and exposure. A robust database of gene expression in free-ranging and managed dolphins across seasons with known adverse health conditions or contaminant exposures will be needed to establish predictive gene expression profiles suitable for biomonitoring.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-3020-8) contains supplementary material, which is available to authorized users.

Standardized Whole-Blood Transcriptional Profiling Enables the Deconvolution of Complex Induced Immune Responses

Systems approaches for the study of immune signaling pathways have been traditionally based on purified cells or cultured lines. However, in vivo responses involve the coordinated action of multiple cell types, which interact to establish an inflammatory microenvironment. We employed standardized whole-blood stimulation systems to test the hypothesis that responses to Toll-like receptor ligands or whole microbes can be defined by the transcriptional signatures of key cytokines. We found 44 genes, identified using Support Vector Machine learning, that captured the diversity of complex innate immune responses with improved segregation between distinct stimuli. Furthermore, we used donor variability to identify shared inter-cellular pathways and trace cytokine loops involved in gene expression. This provides strategies for dimension reduction of large datasets and deconvolution of innate immune responses applicable for characterizing immunomodulatory molecules. Moreover, we provide an interactive R-Shiny application with healthy donor reference values for induced inflammatory genes.

Globin mRNA reduction for whole-blood transcriptome sequencing

The transcriptome analysis of whole-blood RNA by sequencing holds promise for the identification and tracking of biomarkers; however, the high globin mRNA (gmRNA) content of erythrocytes hampers whole-blood and buffy coat analyses. We introduce a novel gmRNA locking assay (GlobinLock, GL) as a robust and simple gmRNA reduction tool to preserve RNA quality, save time and cost. GL consists of a pair of gmRNA-specific oligonucleotides in RNA initial denaturation buffer that is effective immediately after RNA denaturation and adds only ten minutes of incubation to the whole cDNA synthesis procedure when compared to non-blood RNA analysis. We show that GL is fully effective not only for human samples but also for mouse and rat, and so far incompletely studied cow, dog and zebrafish.

Evaluation of the External RNA Controls Consortium (ERCC) reference material using a modified Latin square design

BACKGROUND

Highly multiplexed assays for quantitation of RNA transcripts are being used in many areas of biology and medicine. Using data generated by these transcriptomic assays requires measurement assurance with appropriate controls. Methods to prototype and evaluate multiple RNA controls were developed as part of the External RNA Controls Consortium (ERCC) assessment process. These approaches included a modified Latin square design to provide a broad dynamic range of relative abundance with known differences between four complex pools of ERCC RNA transcripts spiked into a human liver total RNA background.

RESULTS

ERCC pools were analyzed on four different microarray platforms: Agilent 1- and 2-color, Illumina bead, and NIAID lab-made spotted microarrays; and two different second-generation sequencing platforms: the Life Technologies 5500xl and the Illumina HiSeq 2500. Individual ERCC controls were assessed for reproducible performance in signal response to concentration among the platforms. Most demonstrated linear behavior if they were not located near one of the extremes of the dynamic range. Performance issues with any individual ERCC transcript could be attributed to detection limitations, platform-specific target probe issues, or potential mixing errors. Collectively, these pools of spike-in RNA controls were evaluated for suitability as surrogates for endogenous transcripts to interrogate the performance of the RNA measurement process of each platform. The controls were useful for establishing the dynamic range of the assay, as well as delineating the useable region of that range where differential expression measurements, expressed as ratios, would be expected to be accurate.

CONCLUSIONS

The modified Latin square design presented here uses a composite testing scheme for the evaluation of multiple performance characteristics: linear performance of individual controls, signal response within dynamic range pools of controls, and ratio detection between pairs of dynamic range pools. This compact design provides an economical sample format for the evaluation of multiple external RNA controls within a single experiment per platform. These results indicate that well-designed pools of RNA controls, spiked into samples, provide measurement assurance for endogenous gene expression studies.

Depletion of Abundant Sequences by Hybridization (DASH): using Cas9 to remove unwanted high-abundance species in sequencing libraries and molecular counting applications

Next-generation sequencing has generated a need for a broadly applicable method to remove unwanted high-abundance species prior to sequencing. We introduce DASH (Depletion of Abundant Sequences by Hybridization). Sequencing libraries are 'DASHed' with recombinant Cas9 protein complexed with a library of guide RNAs targeting unwanted species for cleavage, thus preventing them from consuming sequencing space. We demonstrate a more than 99 % reduction of mitochondrial rRNA in HeLa cells, and enrichment of pathogen sequences in patient samples. We also demonstrate an application of DASH in cancer. This simple method can be adapted for any sample type and increases sequencing yield without additional cost.

Inter-Individual Differences in RNA Levels in Human Peripheral Blood

Relatively little is known about the range of RNA levels in human blood. This report provides assessment of peripheral blood RNA level and its inter-individual differences in a group of 35 healthy humans consisting of 25 females and 10 males ranging in age from 50 to 89 years. In this group, the average total RNA level was 14.59 μg/ml of blood, with no statistically significant difference between females and males. The individual RNA level ranged from 6.7 to 22.7 μg/ml of blood. In healthy subjects, the repeated sampling of an individual’s blood showed that RNA level, whether high or low, was stable. The inter-individual differences in RNA level in blood can be attributed to both, differences in cell number and the amount of RNA per cell. The 3.4-fold range of inter-individual differences in total RNA levels, documented herein, should be taken into account when evaluating the results of quantitative RT-PCR and/or RNA sequencing studies of human blood. Based on the presented results, a comprehensive assessment of gene expression in blood should involve determination of both the amount of mRNA per unit of total RNA (U / ng RNA) and the amount of mRNA per unit of blood (U / ml blood) to assure a thorough interpretation of physiological or pathological relevance of study results.