RNA-seq Methods Research Articles

Transcriptional adaptation of Mycobacterium tuberculosis that survives prolonged multi-drug treatment in mice.

A major reason that curing tuberculosis requires prolonged treatment is that drug exposure changes bacterial phenotypes. The physiologic adaptations of Mycobacterium tuberculosis that survive drug exposure in vivo have been obscure due to low sensitivity of existing methods in drug-treated animals. Using the novel SEARCH-TB RNA-seq platform, we elucidated Mycobacterium tuberculosis phenotypes in mice treated for with the global standard 4-drug regimen and compared them with the effect of the same regimen in vitro. This first view of the transcriptome of the minority Mycobacterium tuberculosis population that withstands treatment in vivo reveals adaptation of a broad range of cellular processes, including a shift in metabolism and cell wall modification. Surprisingly, the change in gene expression induced by treatment in vivo and in vitro was largely similar. This apparent "portability" from in vitro to the mouse provides important new context for in vitro transcriptional analyses that may support early preclinical drug evaluation.

Identification and quantification of small exon-containing isoforms in long-read RNA sequencing data.

Small exons are pervasive in transcriptomes across organisms, and their quantification in RNA isoforms is crucial for understanding gene functions. Although long-read RNA-seq based on Oxford Nanopore Technologies (ONT) offers the advantage of covering transcripts in full length, its lower base accuracy poses challenges for identifying individual exons, particularly microexons (≤30 nucleotides). Here, we systematically assess small exons quantification in synthetic and human ONT RNA-seq datasets. We demonstrate that reads containing small exons are often not properly aligned, affecting the quantification of relevant transcripts. Thus, we develop a local-realignment method for misaligned exons (MisER), which remaps reads with misaligned exons to the transcript references. Using synthetic and simulated datasets, we demonstrate the high sensitivity and specificity of MisER for the quantification of transcripts containing small exons. Moreover, MisER enabled us to identify small exons with a higher percent spliced-in index (PSI) in neural, particularly neural-regulated microexons, when comparing 14 neural to 16 non-neural tissues in humans. Our work introduces an improved quantification method for long-read RNA-seq and especially facilitates studies using ONT long-reads to elucidate the regulation of genes involving small exons.

Single-Molecule Poly(A) Tail Sequencing (SM-PATseq) Using the PacBio Platform.

The polyadenylation of the 3' ends of messenger RNAs is an important regulator of stability and translation. We developed the single-molecule poly(A) tail sequencing method, SM-PATseq, to assay tail lengths of the whole transcriptome at nucleotide resolution using long-read sequencing. This method generates cDNA using an oligo-dT 3' splint adaptor ligation to prime first-strand cDNA synthesis, followed by random hexamer priming for second-strand synthesis. By directly sequencing the cDNA on long-read platforms, we can resolve tail lengths at nucleotide resolution, identify non-A bases within the tail, and quantify transcript abundance analogous to traditional RNAseq methods. Here, we discuss the method for generating, sequencing, and primary analysis of poly(A) tail data from total RNA using the Pacific Biosciences Sequel platform.

Integrative analysis reveals early epigenetic alterations in high-grade serous ovarian carcinomas.

High-grade serous ovarian carcinoma (HGSOC) is the most lethal gynecological malignancy. To date, the profiles of gene mutations and copy number alterations in HGSOC have been well characterized. However, the patterns of epigenetic alterations and transcription factor dysregulation in HGSOC have not yet been fully elucidated. In this study, we performed integrative omics analyses of a series of stepwise HGSOC model cells originating from human fallopian tube secretory epithelial cells (HFTSECs) to investigate early epigenetic alterations in HGSOC tumorigenesis. Assay for transposase-accessible chromatin using sequencing (ATAC-seq), chromatin immunoprecipitation sequencing (ChIP-seq), and RNA sequencing (RNA-seq) methods were used to analyze HGSOC samples. Additionally, protein expression changes in target genes were confirmed using normal HFTSECs, serous tubal intraepithelial carcinomas (STICs), and HGSOC tissues. Transcription factor motif analysis revealed that the DNA-binding activity of the AP-1 complex and GATA family proteins was dysregulated during early tumorigenesis. The protein expression levels of JUN and FOSL2 were increased, and those of GATA6 and DAB2 were decreased in STIC lesions, which were associated with epithelial-mesenchymal transition (EMT) and proteasome downregulation. The genomic region around the FRA16D site, containing a cadherin cluster region, was epigenetically suppressed by oncogenic signaling. Proteasome inhibition caused the upregulation of chemokine genes, which may facilitate immune evasion during HGSOC tumorigenesis. Importantly, MEK inhibitor treatment reversed these oncogenic alterations, indicating its clinical effectiveness in a subgroup of patients with HGSOC. This result suggests that MEK inhibitor therapy may be an effective treatment option for chemotherapy-resistant HGSOC.

Integrative Transcriptomics and Proteomics Analysis Reveals Immune Response Process in Bovine Viral Diarrhea Virus-1-Infected Peripheral Blood Mononuclear Cells.

Bovine viral diarrhea virus (BVDV) causes bovine viral diarrhea-mucosal disease, inflicting substantial economic losses upon the global cattle industry. Peripheral blood mononuclear cells (PBMCs) are the central hub for immune responses during host-virus infection and have been recognized as crucial targets for BVDV infection. In order to elucidate the dynamics of host-BVDV-1 interaction, this study harnessed RNA-seq and iTRAQ methods to acquire an extensive dataset of transcriptomics and proteomics data from samples of BVDV-1-infected PBMCs at the 12-h post-infection mark. When compared to mock-infected PBMCs, we identified 344 differentially expressed genes (DEGs: a total of 234 genes with downregulated expression and 110 genes with upregulated expression) and 446 differentially expressed proteins (DEPs: a total of 224 proteins with downregulated expression and 222 proteins with upregulated expression). Selected DEGs and DEPs were validated through quantitative reverse transcriptase-polymerase chain reaction and parallel reaction monitoring. Gene ontology annotation and KEGG enrichment analysis underscored the significant enrichment of DEGs and DEPs in various immunity-related signaling pathways, including antigen processing and presentation, complement and coagulation cascades, cytokine-cytokine receptor interaction, and the NOD-like receptor signaling pathway, among others. Further analysis unveiled that those DEGs and DEPs with downregulated expression were predominantly associated with pathways such as complement and coagulation cascades, the interleukin-17 signaling pathway, cytokine-cytokine receptor interaction, the PI3K-Akt signaling pathway, the tumor necrosis factor signaling pathway, and the NOD-like receptor signaling pathway. Conversely, upregulated DEGs and DEPs were chiefly linked to metabolic pathways, oxidative phosphorylation, complement and coagulation cascades, and the RIG-I-like receptor signaling pathway. These altered genes and proteins shed light on the intense host-virus conflict within the immune realm. Our transcriptomics and proteomics data constitute a significant foundation for delving further into the interaction mechanism between BVDV and its host.

CLT-seq as a universal homopolymer-sequencing concept reveals poly(A)-tail-tuned ncRNA regulation.

Dynamic tuning of the poly(A) tail is a crucial mechanism for controlling translation and stability of eukaryotic mRNA. Achieving a comprehensive understanding of how this regulation occurs requires unbiased abundance quantification of poly(A)-tail transcripts and simple poly(A)-length measurement using high-throughput sequencing platforms. Current methods have limitations due to complicated setups and elaborate library preparation plans. To address this, we introduce central limit theorem (CLT)-managed RNA-seq (CLT-seq), a simple and straightforward homopolymer-sequencing method. In CLT-seq, an anchor-free oligo(dT) primer rapidly binds to and unbinds from anywhere along the poly(A) tail string, leading to position-directed reverse transcription with equal probability. The CLT mechanism enables the synthesized poly(T) lengths, which correspond to the templated segment of the poly(A) tail, to distribute normally. Based on a well-fitted pseudogaussian-derived poly(A)-poly(T) conversion model, the actual poly(A)-tail profile is reconstructed from the acquired poly(T)-length profile through matrix operations. CLT-seq follows a simple procedure without requiring RNA-related pre-treatment, enrichment or selection, and the CLT-shortened poly(T) stretches are more compatible with existing sequencing platforms. This proof-of-concept approach facilitates direct homopolymer base-calling and features unbiased RNA-seq. Therefore, CLT-seq provides unbiased, robust and cost-efficient transcriptome-wide poly(A)-tail profiling. We demonstrate that CLT-seq on the most common Illumina platform delivers reliable poly(A)-tail profiling at a transcriptome-wide scale in human cellular contexts. We find that the poly(A)-tail-tuned ncRNA regulation undergoes a dynamic, complex process similar to mRNA regulation. Overall, CLT-seq offers a simplified, effective and economical approach to investigate poly(A)-tail regulation, with potential implications for understanding gene expression and identifying therapeutic targets.

Long-read sequencing reveals the landscape of aberrant alternative splicing and novel therapeutic target in colorectal cancer

BackgroundAlternative splicing complexity plays a vital role in carcinogenesis and cancer progression. Improved understanding of novel splicing events and the underlying regulatory mechanisms may contribute new insights into developing new therapeutic strategies for colorectal cancer (CRC).MethodsHere, we combined long-read sequencing technology with short-read RNA-seq methods to investigate the transcriptome complexity in CRC. By using experiment assays, we explored the function of newly identified splicing isoform TIMP1 Δ4-5. Moreover, a CRISPR/dCasRx-based strategy to induce the TIMP1 exon 4–5 exclusion was introduced to inhibit neoplasm growth.ResultsA total of 90,703 transcripts were identified, of which > 62% were novel compared with current transcriptome annotations. These novel transcripts were more likely to be sample specific, expressed at relatively lower levels with more exons, and oncogenes displayed a characteristic to generate more transcripts in CRC. Clinical outcome data analysis showed that 1472 differentially expressed alternative splicing events (DEAS) were tightly associated with CRC patients’ prognosis, and many novel isoforms were likely to be important determinants for patient survival. Among these, newly identified splicing isoform TIMP1 Δ4-5 was significantly downregulated in CRC. Further in vitro and in vivo assays demonstrated that ectopic expression of TIMP1 Δ4-5 significantly suppresses tumor cell growth and metastasis. Serine/arginine-rich splicing factor 1 (SRSF1) acts as a onco-splicing regulator through sustaining the inclusion of TIMP1 exon 4–5. Furthermore, CRISPR/dCasRx-based strategies designed to induce TIMP1 exon 4–5 exclusion have the potential to restrain the CRC growth.ConclusionsThis data provides a rich resource for deeper studies of gastrointestinal malignancies. Newly identified splicing isoform TIMP1 Δ4-5 plays an important role in mediating CRC progression and may be a potential therapy target in CRC.

Analysis of plant expression profiles revealed that aphid attack triggered dynamic defense responses in sorghum plant.

Sorghum [Sorghum bicolor (L.) Moench] is one of the most important cereal crops grown worldwide but is often attacked by greenbug (aphid). In response to aphid attack, host plant initiates a large transcriptional reorganization, leading to activation of the host defense genes in aphid-attacked plants. In this study, our objective was to analyze defensive responses of sorghum against aphid and identify aphid resistance genes in sorghum. For the experiments, seedlings developed from an aphid resistant germplasm line (PI 550607) were divided into two groups, then, one group was infested with greenbug ((Schizaphis graminum Rondani) and the other group was used as control (un-infested). In addition, seedlings of sorghum cultivar Tx 7000, a susceptible genotype, prepared under the same conditions, were used as a genetic control. Those plant samples were used to develop transcriptional profiles using the microarray method, from which 26.1% of the 1,761 cDNA sequences spotted on the microarray showed altered expression between two treatments at 4days after infestation. Sequence annotation and molecular analysis revealed that many differentially expressed genes (DEGs) were related to direct host defense or signal transduction pathways, which regulate host defense. In addition to common responsive genes, unique transcripts were identified in response to greenbug infestation specifically. Later, a similar transcriptional profiling was conducted using the RNA-seq method, resulted in the identification of 2,856 DEGs in the resistant line with a comparison between infested and non-infested at 4days and 4,354 DEGs in the resistant genotype compared to the susceptible genotype at 4days. Based on the comparative analysis, the data of RNA-seq provided a support for the results from the microarray study as it was noticed that many of the DEGs are common in both platforms. Analysis of the two differential expression profiles indicate that aphid triggered dynamic defense responses in sorghum plants and sorghum plant defense against aphid is a complex process involving both general defense systems and specific resistance mechanisms. Finally, the results of the study provide new insights into the mechanisms underlying host plant defense against aphids and will help us design better strategies for effectively controlling aphid pest.

Transcriptomic and behavioral studies reveal that glutamate receptors are involved in depressive-like behavior in adult olive flounder Paralichthys olivaceus

Olive flounder (Paralichthys olivaceus), a marine demersal flatfish species, exhibits obvious timid and depressive-like characteristics. Adult olive flounder bury themselves in the sand and present motionless behavior. However, the detail mechanism of regulating the motionless behavior is not fully understood. In this study, using adult group (AG) and juvenile group (JG) flounder as a model, we compared the locomotor activity of AG and JG flounder, and analyzed the transcriptomic expression profiles in the spinal cord by RNA-seq methods. The behavioral experiment showed that AG flounder displayed lower locomotor activity. Transcriptome analysis found a total of 1711 significantly differential expressed genes (DEGs), among which 818 genes were up-regulated and 893 genes were down-regulated in AG flounder compared with JG flounder. Specifically, locomotor behavior related genes (parvalbumin, urotensin II and creatine kinase) were down-regulated. Meanwhile glial fibrillary acidic protein, the biomarkers of astroglial pathology, and glutamatergic synaptic genes were significantly up-regulated in AG flounder. In addition, Gene Ontology (GO) enrichment analysis revealed that DEGs enriched in peptide biosynthetic process, translation procession were down-regulated in the AG flounder. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that ribosome, oxidative phosphorylation and glutamatergic synapse pathway were over-represented. After treatment with antagonist of glutamate receptor LY341495, flounder more often swam out of the sand and displayed significantly more off-bottom swimming behavior, suggesting the anti-depressive effect of LY341495. Taken together, in combination with behavioral tests and transcriptomic analyses, we conclude that the glutamate receptor in spinal cord plays an important role in timid and depressive-like behavior in flounder.

Genome-Wide Identification and Characterization of the TLP Gene Family in Phyllostachys edulis and Association with Witches' Broom Disease Resistance in Bamboo.

Thaumatin-like proteins (TLPs) are pathogenesis-related proteins with pivotal roles in plant defense mechanisms. In this study, various bioinformatics and RNA-seq methods were used to analyze the biotic and abiotic stress responses of the TLP family in Phyllostachys edulis. Overall, 81 TLP genes were identified in P. edulis; 166 TLPs from four plant species were divided into three groups and ten subclasses, with genetic covariance observed between these species. Subcellular localization in silico studies indicated that TLPs were primarily distributed in the extracellular. Analysis of the upstream sequences of TLPs demonstrated the presence of cis-acting elements related to disease defense, environmental stress, and hormonal responses. Multiple sequence alignment demonstrated that most TLPs possessed five conserved REDDD amino acid sequences with only a few amino acid residue differences. RNA-seq analysis of P. edulis responses to Aciculosporium take, the pathogenic fungus that causes witches' broom disease, showed that P. edulis TLPs (PeTLPs) were expressed in different organs, with the highest expression in buds. PeTLPs responded to both abscisic acid and salicylic acid stress. These PeTLP expression patterns were consistent with their gene and protein structures. Collectively, our findings provide a basis for further comprehensive analyses of the genes related to witches' broom in P. edulis.

Different transcription of novel, functional long non-coding RNA genes by UV-B in green algae, Volvox carteri.

Long non-coding RNAs (lncRNAs) are identified as important regulatory molecules related to diverse biological processes. In recent years, benefiting from the rapid development of high-throughput sequencing technology, RNA-seq, and analysis methods, more lncRNAs have been identified and discovered in various plant and algal species. However, so far, only limited studies related to algal lncRNAs are available. Volvox carteri f. nagariensis is the best multicellular model organism to study in developmental and evolutionary biology; therefore, studying and increasing information about this species is important. This study identified lncRNAs in the multicellular green algae Volvox carteri and 1457 lncRNAs were reported, using RNA-seq data and with the help of bioinformatics tools and software. This study investigated the effect of low-dose UV-B radiation on changes in the expression profile of lncRNAs in gonidial and somatic cells. The differential expression of lncRNAs was analyzed between the treatment (UV-B) and the control (WL) groups in gonidial and somatic cells. A total of 37 and 26 lncRNAs with significant differential expression in gonidial and somatic cells, respectively, were reported. Co-expression analysis between the lncRNAs and their neighbor protein-coding genes (in the interval of ± 10Kb) was accomplished. In gonidial cells, 184 genes with a positive correlation and 13 genes with a negative correlation (greater than 0.95), and in somatic cells, 174 genes with a positive correlation, and 18 genes with a negative correlation were detected. Functional analysis of neighboring coding genes was also performed based on gene ontology. The results of the current work may help gain deeper insight into the regulation of gene expression in the studied model organism, Volvox carteri.

A robust and accurate method to detect MET Exon 14–skipping mutation in pan-cancer samples using an NGS-based RNAseq approach.

e20575 Background: Met exon 14 skipping mutation(METex14) occurs in multiple cancer species, mainly in non-small cell lung cancer (NSCLC, 3~4%) and pulmonary sarcomatoid carcinoma (PSC, 22%). Several drugs expressed curative effect in previously treated patients who harboring METex14, such as savolitinib approved by NMPA, capmatinib and tepotinib licenced by FDA. Developing a quick and precise method which detect METex14 and help patients benefit from clinical drug treatment is a desiderative issue currently. Previous researches suggest that transcriptome-based RNA-seq method was superior to DNA-based NGS (exome, panel) and PCR method. Here We introduce a fast and accurate method to detect METex14 alternation in RNAseq data. Methods: We sequenced NGS-based Ribo-zero RNAseq (pair-end, 150bp×2) and METex14 ddPCR on 99 pan-cancer samples, of which 38 lung carcinoma (38%), 8 renal carcinoma (8%), 7 pancreatic carcinoma (7%). In 38 lung carcinoma, 35 NSCLC samples were consist by 29 lung adenocarcinoma (LUAD, 76%), 4 lung squamous carcinoma (LUSC, 10%) and 2 PSC (5%). Begin of the study, data quality control applied by Fastp and aligned to human hg19 genome by STAR subsequently. Next, MET exon14 related candidate soft-clipping reads were extracted from BAM files and translated to fastq file. Then we remapped the translated fastq file to hg19 genome with Blat using parameters ‘stepSize = 5, -repMatch = 2253, -minScore = 20, -minIdentity = 90’. Next, supporting reads were sequentially retained by: single end length longer than 18bp; block mapped reads of MET gene; the pair end reads mapped to genome if one end fall in the last 3bp of MET intron 13 and another end fall in at least initial 3bp of MET exon 15. Pair or single end support junction read, distance of junction site to reads end and site coverage were enrolled in a bayesian model to calculate METex14 confidence score (BMMETs). Threshold of our model was defined by the cut-point of max youden-index and 16 samples were validated METex14 by ddPCR. Finally, we would predict a sample with METex14 when score > = 0.752. Results: Our method reported 15 TP samples, 1 FP sample and 1 FN samples (AUC 0.97, sensitivity 0.88, specificity 0.98) while STAR-fusion detected 14 TR samples and 6 FP sample and 2 FN samples (AUC 0.715, sensitivity 0.64, specificity 0.73). BMMETs FP sample scored approximately 0.739 that close to the threshold. Conclusions: Strategy of screen reliable METex14 supporting reads and using bayesian model to calculate a METex14 confidence score could robustly and efficiently predict METex14 event in NGS-based RNAseq data.

Methanol fixation is the method of choice for droplet-based single-cell transcriptomics of neural cells

The main critical step in single-cell transcriptomics is sample preparation. Several methods have been developed to preserve cells after dissociation to uncouple sample handling from library preparation. Yet, the suitability of these methods depends on the cell types to be processed. In this project, we perform a systematic comparison of preservation methods for droplet-based single-cell RNA-seq on neural and glial cells derived from induced pluripotent stem cells. Our results show that while DMSO provides the highest cell quality in terms of RNA molecules and genes detected per cell, it strongly affects the cellular composition and induces the expression of stress and apoptosis genes. In contrast, methanol fixed samples display a cellular composition similar to fresh samples and provide a good cell quality and little expression biases. Taken together, our results show that methanol fixation is the method of choice for performing droplet-based single-cell transcriptomics experiments on neural cell populations.

Modeling group heteroscedasticity in single-cell RNA-seq pseudo-bulk data

Group heteroscedasticity is commonly observed in pseudo-bulk single-cell RNA-seq datasets and its presence can hamper the detection of differentially expressed genes. Since most bulk RNA-seq methods assume equal group variances, we introduce two new approaches that account for heteroscedastic groups, namely voomByGroup and voomWithQualityWeights using a blocked design (voomQWB). Compared to current gold-standard methods that do not account for group heteroscedasticity, we show results from simulations and various experiments that demonstrate the superior performance of voomByGroup and voomQWB in terms of error control and power when group variances in pseudo-bulk single-cell RNA-seq data are unequal.

Rapid viral metagenomics using SMART-9N amplification and nanopore sequencing.

Emerging and re-emerging viruses are a global health concern. Genome sequencing as an approach for monitoring circulating viruses is currently hampered by complex and expensive methods. Untargeted, metagenomic nanopore sequencing can provide genomic information to identify pathogens, prepare for or even prevent outbreaks. SMART (Switching Mechanism at the 5' end of RNA Template) is a popular approach for RNA-Seq but most current methods rely on oligo-dT priming to target polyadenylated mRNA molecules. We have developed two random primed SMART-Seq approaches, a sequencing agnostic approach 'SMART-9N' and a version compatible rapid adapters available from Oxford Nanopore Technologies 'Rapid SMART-9N'. The methods were developed using viral isolates, clinical samples, and compared to a gold-standard amplicon-based method. From a Zika virus isolate the SMART-9N approach recovered 10kb of the 10.8kb RNA genome in a single nanopore read. We also obtained full genome coverage at a high depth coverage using the Rapid SMART-9N, which takes only 10 minutes and costs up to 45% less than other methods. We found the limits of detection of these methods to be 6 focus forming units (FFU)/mL with 99.02% and 87.58% genome coverage for SMART-9N and Rapid SMART-9N respectively. Yellow fever virus plasma samples and SARS-CoV-2 nasopharyngeal samples previously confirmed by RT-qPCR with a broad range of Ct-values were selected for validation. Both methods produced greater genome coverage when compared to the multiplex PCR approach and we obtained the longest single read of this study (18.5 kb) with a SARS-CoV-2 clinical sample, 60% of the virus genome using the Rapid SMART-9N method. This work demonstrates that SMART-9N and Rapid SMART-9N are sensitive, low input, and long-read compatible alternatives for RNA virus detection and genome sequencing and Rapid SMART-9N improves the cost, time, and complexity of laboratory work.

Using RNA-seq to identify suitable housekeeping genes for hypoxia studies in human adipose-derived stem cells

BackgroundHypoxic culture conditions have been used to study the impact of oxygen deprivation has on gene expression in a number of disease models. However, hypoxia response elements present in the promoter regions of some commonly used housekeeping genes, such as GAPDH and PGK1, can confound the relative gene expression analysis. Thus, there is ongoing debate as to which housekeeping gene is appropriate for studies investigating hypoxia-induced cell responses. Specifically, there is still contradicting information for which housekeeping genes are stable in hypoxia cultures of mesenchymal stem cells. In this study, candidate housekeeping genes curated from the literature were matched to RNAseq data of normoxic and hypoxic human adipose-derived stem cell cultures to determine if gene expression was modulated by hypoxia or not. Expression levels of selected candidates were used to calculate coefficient of variation. Then, accounting for the mean coefficient of variation, and normalised log twofold change, genes were ranked and shortlisted, before validating with qRT-PCR. Housekeeping gene suitability were then determined using GeNorm, NormFinder, BestKeeper, comparativeDelta Ct, RefFinder, and the Livak method.ResultsGene expression levels of 78 candidate genes identified in the literature were analysed in the RNAseq dataset generated from hADSC cultured under Nx and Hx conditions. From the dataset, 15 candidates with coefficient of variation ≤ 0.15 were identified, where differential expression analysis results further shortlisted 8 genes with least variation in expression levels. The top 4 housekeeping gene candidates, ALAS1, RRP1, GUSB, and POLR2B, were chosen for qRT-PCR validation. Additionally, 18S, a ribosomal RNA commonly used as housekeeping gene but not detected in the RNAseq method, was added to the list of housekeeping gene candidates to validate. From qRT-PCR results, 18S and RRP1 were determined to be stably expressed in cells cultured under hypoxic conditions.ConclusionsWe have demonstrated that 18S and RRP1 are suitable housekeeping genes for use in hypoxia studies with human adipose-derived stem cell and should be used in combination. Additionally, these data shown that the commonly used GAPDH and PGK1 are not suitable housekeeping genes for investigations into the effect of hypoxia in human adipose-derived stem cell.

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

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

BakR: uncovering differential RNA synthesis and degradation kinetics transcriptome-wide with Bayesian hierarchical modeling.

Differential expression analysis of RNA sequencing (RNA-seq) data can identify changes in cellular RNA levels, but provides limited information about the kinetic mechanisms underlying such changes. Nucleotide recoding RNA-seq methods (NR-seq; e.g., TimeLapse-seq, SLAM-seq, etc.) address this shortcoming and are widely used approaches to identify changes in RNA synthesis and degradation kinetics. While advanced statistical models implemented in user-friendly software (e.g., DESeq2) have ensured the statistical rigor of differential expression analyses, no such tools that facilitate differential kinetic analysis with NR-seq exist. Here, we report the development of Bayesian analysis of the kinetics of RNA (bakR; https:// github.com/simonlabcode/bakR), an R package to address this need. bakR relies on Bayesian hierarchical modeling of NR-seq data to increase statistical power by sharing information across transcripts. Analyses of simulated data confirmed that bakR implementations of the hierarchical model outperform attempts to analyze differential kinetics with existing models. bakR also uncovers biological signals in real NR-seq data sets and provides improved analyses of existing data sets. This work establishes bakR as an important tool for identifying differential RNA synthesis and degradation kinetics.

TRACE-seq: Rapid, Low-Input, One-Tube RNA-seq Library Construction Based on Tagmentation of RNA/DNA Hybrids.

Tn5 transposase has been widely used to simultaneously fragment and tag double-stranded DNA (dsDNA) with sequencing adaptors in library construction for next-generation sequencing. Recently, we demonstrated that Tn5 transposase also possesses tagmentation activity toward RNA/DNA hybrids, in addition to its canonical dsDNA substrates. Based on this new activity, we are able to skip multiple laborious and time-consuming steps in traditional RNA-seq methods, and rapid, low-input, cost-effective, one-tube RNA-seq library construction is thus enabled. The libraries constructed by Transposase-assisted RNA/DNA hybrids Co-tagmEntation (termed "TRACE-seq") demonstrate excellent performance in terms of gene expression measurement and differential gene expression analysis. Here, we present detailed protocols for TRACE-seq that will be broadly useful for the study of RNA biology and biomedical research. © 2023 Wiley Periodicals LLC. Basic Protocol 1: Total RNA preparation Basic Protocol 2: TRACE-seq library construction Support Protocol: Tn5 transposome assembly.

Revealing the Inhibition of Tea Cultivar ‘Ziyan’ Root Growth Caused by High Nitrogen Based on Physiological, Metabolite, and Transcriptome Analyses

Nitrogen (N) is a key regulator in the growth of tea plants and the synthesis of amino acids (AAs) and related secondary metabolites, thus affecting the yield and quality of tea leaves. Increased N fertilization significantly improves the yield and quality of tea plants, but applying excess nitrogen wastes resources and causes pollution problems. Herein, we employed morphological, physiological, metabolomic, and RNA-seq methods to study the response of ‘Ziyan’ roots to high N. High N supply induced an increase in arginine (Arg), asparagine (Asn), and glutamine (Gln) in roots and simultaneously decreased sucrose, polyphenols, and caffeine contents. High N reduced the length, volume, number, and activity of the roots by 10.63%, 25.00%, 26.95%, and 14.50%, respectively, which inhibited ‘Ziyan’ root growth, probably by disturbing the regulation of carbon and nitrogen metabolism in the tea plant. According to the Kyoto Encyclopedia of Genes and Genome (KEGG) enrichment analysis, AAs, flavonoids, and flavonol-related pathways were relatively active after supplying high N. In addition, the transcriptome analysis identified NRT1/PTR and GOGAT as key genes, and the transcription factors (e.g., AP2/ERF, MYB, and WRKY) and auxins were actively involved in the high N stress response of ‘Ziyan’ roots. These findings will help us understand the adaptive mechanism of high N supply in tea tree roots and provide a reference for guiding the fertilization of ‘Ziyan’ tea plants.