Ribo-Zero Gold Kit: improved RNA-seq results after removal of cytoplasmic and mitochondrial ribosomal RNA

Whole-transcriptome RNA sequencing reveals CeRNA regulatory network under long-term space composite stress in Rats

To systematically evaluate the effect of simulated long-term spaceflight composite stress (LSCS) in hippocampus and gain more insights into the transcriptomic landscape and molecular mechanism, we performed whole-transcriptome sequencing based on the control group (Ctrl) and the simulated long-term spaceflight composite stress group (LSCS) from six hippocampus of rats. Subsequently, differential expression analysis was performed on the Ctrl and LSCS groups, followed by enrichment analysis and functional interaction prediction analysis to investigate gene-regulatory circuits in LSCS. In addition, competitive endogenous RNA (ceRNA) network was constructed to gain insights into genetic interaction. The result showed that 276 differentially expressed messenger RNAs (DEmRNAs), 139 differentially expressed long non-coding RNAs (DElncRNAs), 103 differentially expressed circular RNAs (DEcircRNAs), and 52 differentially expressed microRNAs (DEmiRNAs) were found in LSCS samples compared with the controls, which were then subjected to enrichment analysis of Gene Ontology (GO) term and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways to find potential functions. PI3K-Akt signaling pathway and MAPK signaling pathway may play fundamental roles in the pathogenesis of LSCS. A ceRNA network was constructed with the predicted 340 DE pairs, which revealed the interaction roles of 220 DEmiRNA-DEmRNA pairs, 76 DEmiRNA-DElncRNA pairs, and 44 DEmiRNA-DEcircRNA pairs. Further, Thrombospondins2 was found to be a key target among those ceRNAs. Overall, we conducted for the first time a full transcriptomic analysis of the response of hippocampus to the LSCS that involved a potential ceRNA network, thus providing a basis to study the underlying mechanism of the LSCS.

Benchmark of cellular deconvolution methods using a multi-assay reference dataset from postmortem human prefrontal cortex

Background

Cellular deconvolution of bulk RNA-sequencing (RNA-seq) data using single cell or nuclei RNA-seq (sc/snRNA-seq) reference data is an important strategy for estimating cell type composition in heterogeneous tissues, such as human brain. Computational methods for deconvolution have been developed and benchmarked against simulated data, pseudobulked sc/snRNA-seq data, or immunohistochemistry reference data. A major limitation in developing improved deconvolution algorithms has been the lack of integrated datasets with orthogonal measurements of gene expression and estimates of cell type proportions on the same tissue sample. Deconvolution algorithm performance has not yet been evaluated across different RNA extraction methods (cytosolic, nuclear, or whole cell RNA), different library preparation types (mRNA enrichment vs. ribosomal RNA depletion), or with matched single cell reference datasets.

Results

A rich multi-assay dataset was generated in postmortem human dorsolateral prefrontal cortex (DLPFC) from 22 tissue blocks. Assays included spatially-resolved transcriptomics, snRNA-seq, bulk RNA-seq (across six library/extraction RNA-seq combinations), and RNAScope/Immunofluorescence (RNAScope/IF) for six broad cell types. The Mean Ratio method, implemented in the DeconvoBuddies R package, was developed for selecting cell type marker genes. Six computational deconvolution algorithms were evaluated in DLPFC and predicted cell type proportions were compared to orthogonal RNAScope/IF measurements.

Conclusions

Bisque and hspe were the most accurate methods, were robust to differences in RNA library types and extractions. This multi-assay dataset showed that cell size differences, marker genes differentially quantified across RNA libraries, and cell composition variability in reference snRNA-seq impact the accuracy of current deconvolution methods.

Dissection of transcriptomic and epigenetic heterogeneity of grade 4 gliomas: implications for prognosis

BACKGROUND

Grade 4 glioma is the most aggressive and currently incurable brain tumor with a median survival of one year in adult patients. Elucidating novel transcriptomic and epigenetic contributors to the molecular heterogeneity underlying its aggressiveness may lead to improved clinical outcomes.

METHODS

To identify grade 4 glioma -associated 5-hydroxymethylcytosine (5hmC) and transcriptomic features as well as their cross-talks, genome-wide 5hmC and transcriptomic profiles of tissue samples from 61 patients with grade 4 gliomas and 9 normal controls were obtained for differential and co-regulation/co-modification analyses. Prognostic models on overall survival based on transcriptomic features and the 5hmC modifications summarized over genic regions (promoters, gene bodies) and brain-derived histone marks were developed using machine learning algorithms.

RESULTS

Despite global reduction, the majority of differential 5hmC features showed higher modification levels in grade 4 gliomas as compared to normal controls. In addition, the bi-directional correlations between 5hmC modifications over promoter regions or gene bodies and gene expression were greatly disturbed in grade 4 gliomas regardless of IDH1 mutation status. Phenotype-associated co-regulated 5hmC-5hmC modules and 5hmC-mRNA modules not only are enriched with different molecular pathways that are indicative of the pathogenesis of grade 4 gliomas, but also are of prognostic significance comparable to IDH1 mutation status. Lastly, the best-performing 5hmC model can predict patient survival at a much higher accuracy (c-index = 74%) when compared to conventional prognostic factor IDH1 (c-index = 57%), capturing the molecular characteristics of tumors that are independent of IDH1 mutation status and gene expression-based molecular subtypes.

CONCLUSIONS

The 5hmC-based prognostic model could offer a robust tool to predict survival in patients with grade 4 gliomas, potentially outperforming existing prognostic factors such as IDH1 mutations. The crosstalk between 5hmC and gene expression revealed another layer of complexity underlying the molecular heterogeneity in grade 4 gliomas, offering opportunities for identifying novel therapeutic targets.

Physiological changes during torpor favor association with Endozoicomonas endosymbionts in the urochordate Botrylloides leachii

Environmental perturbations evoke down-regulation of metabolism in some multicellular organisms, leading to dormancy, or torpor. Colonies of the urochordate Botrylloides leachii enter torpor in response to changes in seawater temperature and may survive for months as small vasculature remnants that lack feeding and reproductive organs but possess torpor-specific microbiota. Upon returning to milder conditions, the colonies rapidly restore their original morphology, cytology and functionality while harboring re-occurring microbiota, a phenomenon that has not been described in detail to date. Here we investigated the stability of B. leachii microbiome and its functionality in active and dormant colonies, using microscopy, qPCR, in situ hybridization, genomics and transcriptomics. A novel lineage of Endozoicomonas, proposed here as Candidatus Endozoicomonas endoleachii, was dominant in torpor animals (53-79% read abundance), and potentially occupied specific hemocytes found only in torpid animals. Functional analysis of the metagenome-assembled genome and genome-targeted transcriptomics revealed that Endozoicomonas can use various cellular substrates, like amino acids and sugars, potentially producing biotin and thiamine, but also expressing various features involved in autocatalytic symbiosis. Our study suggests that the microbiome can be linked to the metabolic and physiological states of the host, B. leachii, introducing a model organism for the study of symbioses during drastic physiological changes, such as torpor.

T-RHEX-RNAseq - a tagmentation-based, rRNA blocked, random hexamer primed RNAseq method for generating stranded RNAseq libraries directly from very low numbers of lysed cells

BACKGROUND

RNA sequencing has become the mainstay for studies of gene expression. Still, analysis of rare cells with random hexamer priming - to allow analysis of a broader range of transcripts - remains challenging.

RESULTS

We here describe a tagmentation-based, rRNA blocked, random hexamer primed RNAseq approach (T-RHEX-RNAseq) for generating stranded RNAseq libraries from very low numbers of FACS sorted cells without RNA purification steps.

CONCLUSION

T-RHEX-RNAseq provides an easy-to-use, time efficient and automation compatible method for generating stranded RNAseq libraries from rare cells.

Blocking Abundant RNA Transcripts by High-Affinity Oligonucleotides during Transcriptome Library Preparation

BACKGROUND

RNA sequencing has become the gold standard for transcriptome analysis but has an inherent limitation of challenging quantification of low-abundant transcripts. In contrast to microarray technology, RNA sequencing reads are proportionally divided in function of transcript abundance. Therefore, low-abundant RNAs compete against highly abundant - and sometimes non-informative - RNA species.

RESULTS

We developed an easy-to-use strategy based on high-affinity RNA-binding oligonucleotides to block reverse transcription and PCR amplification of specific RNA transcripts, thereby substantially reducing their abundance in the final sequencing library. To demonstrate the broad application potential of our method, we applied it to different transcripts and library preparation strategies, including YRNAs in small RNA sequencing of human blood plasma, mitochondrial rRNAs in both 3' end sequencing and long-read sequencing, and MALAT1 in single-cell 3' end sequencing. We demonstrate that the blocking strategy is highly efficient, reproducible, specific, and generally results in better transcriptome coverage and complexity.

CONCLUSION

Our method does not require modifications of the library preparation procedure apart from simply adding blocking oligonucleotides to the RT reaction and can thus be easily integrated into virtually any RNA sequencing library preparation protocol.

The role of OncoSnoRNAs and Ribosomal RNA 2'-O-methylation in Cancer

Ribosomes are essential nanomachines responsible for all protein production in cells. Ribosome biogenesis and function are energy costly processes, they are tightly regulated to match cellular needs. In cancer, major pathways that control ribosome biogenesis and function are often deregulated to ensure cell survival and to accommodate the continuous proliferation of tumour cells. Ribosomal RNAs (rRNAs) are abundantly modified with 2'-O-methylation (Nm, ribomethylation) being one of the most common modifications. In eukaryotic ribosomes, ribomethylation is performed by the methyltransferase Fibrillarin guided by box C/D small nucleolar RNAs (snoRNAs). Accumulating evidences indicate that snoRNA expression and ribosome methylation profiles are altered in cancer. Here we review our current knowledge on differential snoRNA expression and rRNA 2ʹ-O methylation in the context of human malignancies, and discuss the consequences and opportunities for cancer diagnostics, prognostics, and therapeutics.

Metatranscriptomics and Amplicon Sequencing Reveal Mutualisms in Seagrass Microbiomes

Terrestrial plants benefit from many well-understood mutualistic relationships with root- and leaf-associated microbiomes, but relatively little is known about these relationships for seagrass and other aquatic plants. We used 16S rRNA gene amplicon sequencing and metatranscriptomics to assess potential mutualisms between microorganisms and the seagrasses Zostera marina and Zostera japonica collected from mixed beds in Netarts Bay, OR, United States. The phylogenetic composition of leaf-, root-, and water column-associated bacterial communities were strikingly different, but these communities were not significantly different between plant species. Many taxa present on leaves were related to organisms capable of consuming the common plant metabolic waste product methanol, and of producing agarases, which can limit the growth of epiphytic algae. Taxa present on roots were related to organisms capable of oxidizing toxic sulfur compounds and of fixing nitrogen. Metatranscriptomic sequencing identified expression of genes involved in all of these microbial metabolic processes at levels greater than typical water column bacterioplankton, and also identified expression of genes involved in denitrification and in bacterial synthesis of the plant growth hormone indole-3-acetate. These results provide the first evidence using metatranscriptomics that seagrass microbiomes carry out a broad range of functions that may benefit their hosts, and imply that microbe-plant mutualisms support the health and growth of aquatic plants.

A comprehensive transcriptome analysis of skeletal muscles in two Polish pig breeds differing in fat and meat quality traits

Pork is the most popular meat in the world. Unfortunately, the selection pressure focused on high meat content led to a reduction in pork quality. The present study used RNA-seq technology to identify metabolic process genes related to pork quality traits and fat deposition. Differentially expressed genes (DEGs) were identified between pigs of Pulawska and Polish Landrace breeds for two the most important muscles (semimembranosus and longissimus dorsi). A total of 71 significant DEGs were reported: 15 for longissimus dorsi and 56 for semimembranosus muscles. The genes overexpressed in Pulawska pigs were involved in lipid metabolism (APOD, LXRA, LIPE, AP2B1, ENSSSCG00000028753 and OAS2) and proteolysis (CST6, CTSD, ISG15 and UCHL1). In Polish Landrace pigs, genes playing a role in biological adhesion (KIT, VCAN, HES1, SFRP2, CDH11, SSX2IP and PCDH17), actin cytoskeletal organisation (FRMD6, LIMK1, KIF23 and CNN1) and calcium ion binding (PVALB, CIB2, PCDH17, VCAN and CDH11) were transcriptionally more active. The present study allows for better understanding of the physiological processes associated with lipid metabolism and muscle fiber organization. This information could be helpful in further research aiming to estimate the genetic markers.

Cancer transcriptome profiling at the juncture of clinical translation

Methodological breakthroughs over the past four decades have repeatedly revolutionized transcriptome profiling. Using RNA sequencing (RNA-seq), it has now become possible to sequence and quantify the transcriptional outputs of individual cells or thousands of samples. These transcriptomes provide a link between cellular phenotypes and their molecular underpinnings, such as mutations. In the context of cancer, this link represents an opportunity to dissect the complexity and heterogeneity of tumours and to discover new biomarkers or therapeutic strategies. Here, we review the rationale, methodology and translational impact of transcriptome profiling in cancer.

Gene expression analysis of whole blood RNA from pigs infected with low and high pathogenic African swine fever viruses

African swine fever virus (ASFV) is a macrophage-tropic virus responsible for ASF, a transboundary disease that threatens swine production world-wide. Since there are no vaccines available to control ASF after an outbreak, obtaining an understanding of the virus-host interaction is important for developing new intervention strategies. In this study, a whole transcriptomic RNA-Seq method was used to characterize differentially expressed genes in pigs infected with a low pathogenic ASFV isolate, OUR T88/3 (OURT), or the highly pathogenic Georgia 2007/1 (GRG). After infection, pigs infected with OURT showed no or few clinical signs; whereas, GRG produced clinical signs consistent with acute ASF. RNA-Seq detected the expression of ASFV genes from the whole blood of the GRG, but not the OURT pigs, consistent with the pathotypes of these strains and the replication of GRG in circulating monocytes. Even though GRG and OURT possess different pathogenic properties, there was significant overlap in the most upregulated host genes. A small number of differentially expressed microRNAs were also detected in GRG and OURT pigs. These data confirm previous studies describing the response of macrophages and lymphocytes to ASFV infection, as well as reveal unique gene pathways upregulated in response to infection with GRG.

Automated high throughput nucleic acid purification from formalin-fixed paraffin-embedded tissue samples for next generation sequence analysis

Curation and storage of formalin-fixed, paraffin-embedded (FFPE) samples are standard procedures in hospital pathology laboratories around the world. Many thousands of such samples exist and could be used for next generation sequencing analysis. Retrospective analyses of such samples are important for identifying molecular correlates of carcinogenesis, treatment history and disease outcomes. Two major hurdles in using FFPE material for sequencing are the damaged nature of the nucleic acids and the labor-intensive nature of nucleic acid purification. These limitations and a number of other issues that span multiple steps from nucleic acid purification to library construction are addressed here. We optimized and automated a 96-well magnetic bead-based extraction protocol that can be scaled to large cohorts and is compatible with automation. Using sets of 32 and 91 individual FFPE samples respectively, we generated libraries from 100 ng of total RNA and DNA starting amounts with 95–100% success rate. The use of the resulting RNA in micro-RNA sequencing was also demonstrated. In addition to offering the potential of scalability and rapid throughput, the yield obtained with lower input requirements makes these methods applicable to clinical samples where tissue abundance is limiting.