Simple and efficient profiling of transcription initiation and transcript levels with STRIPE-seq.
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ABSTRACT:
SUBMITTER: Policastro RA
PROVIDER: S-EPMC7370879 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Accurate mapping of transcription start sites (TSSs) is key for understanding transcriptional regulation. However, current protocols for genome-wide TSS profiling are laborious and/or expensive. We present Survey of TRanscription Initiation at Promoter Elements with high-throughput sequencing (STRIPE-seq), a simple, rapid, and cost-effective protocol for sequencing capped RNA 5’-ends from as little as 50 ng total RNA. Including depletion of uncapped RNA and SPRI bead cleanups, a STRIPE-seq library can be constructed in approximately four hours. We demonstrate application of STRIPE-seq to TSS profiling in yeast and human cells and show that it can also be effectively used for measuring transcript levels and for differential gene expression analysis. In conjunction with our ready-to-use computational analysis workflows, STRIPE-seq is a straightforward, efficient means by which to probe the landscape of transcriptional initiation.
2020-01-13 | GSE142524 | GEO
Project description:Simple and efficient measurement of transcription initiation and transcript levels with STRIPE-seq
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Project description:T cells create vast amounts of diversity in the genes that encode their T cell receptors (TCRs), which enables individual clones to recognize specific peptide-major histocompatibility complex (MHC) ligands. Here we combined sequencing of the TCR-encoding genes with assay for transposase-accessible chromatin with sequencing (ATAC-seq) analysis at the single-cell level to provide information on the TCR specificity and epigenomic state of individual T cells. By using this approach, termed transcript-indexed ATAC-seq (T-ATAC-seq), we identified epigenomic signatures in immortalized leukemic T cells, primary human T cells from healthy volunteers and primary leukemic T cells from patient samples. In peripheral blood CD4+ T cells from healthy individuals, we identified cis and trans regulators of naive and memory T cell states and found substantial heterogeneity in surface-marker-defined T cell populations. In patients with a leukemic form of cutaneous T cell lymphoma, T-ATAC-seq enabled identification of leukemic and nonleukemic regulatory pathways in T cells from the same individual by allowing separation of the signals that arose from the malignant clone from the background T cell noise. Thus, T-ATAC-seq is a new tool that enables analysis of epigenomic landscapes in clonal T cells and should be valuable for studies of T cell malignancy, immunity and immunotherapy.
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Project description:Kenaf (Hibiscus cannabinus L.) is an economically important global natural fiber crop. As a consequence of the increased demand for food crops and the reduction of available arable land, kenaf cultivation has increasingly shifted to saline and alkaline land. To investigate the molecular mechanism of salinity tolerance in kenaf, we performed Illumina high-throughput RNA sequencing on shoot tips of kenaf and identified 71,318 unigenes, which were annotated using four different protein databases. In total, 2,384 differentially expressed genes (DEGs) were identified between the salt-stressed and the control plants, 1,702 of these transcripts were up-regulated and 683 transcripts were down-regulated. Thirty-seven transcripts belonging to 15 transcription-factor families that respond to salt stress were identified. Gene ontology function enrichment analysis revealed that the genes encoding antioxidant enzymes were up-regulated. The amino acid metabolism and carbohydrate metabolism pathways were highly enriched among these DEGs under salt stress conditions. In order to confirm the RNA-seq data, we randomly selected 20 unigenes for analysis using a quntitative real-time polymerase chain reaction. Our study not only provided the large-scale assessment of transcriptome resources of kenaf but also guidelines for understanding the mechanism underlying salt stress responses in kenaf.
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Project description:Measuring the global gene expression pattern in a single cell has been technically challenging, but is potentially very useful for understanding variation in biological processes between cells and for studying gene regulation during early embryo development with single cell resolution. To advance these applications, multiple systems for single-cell RNA extraction in addition to crude cell lysis followed by RNA profiling were examined and used for genomic data analysis. Our results indicate that some of these methods are suitable for analyzing even a portion of the total RNA from a single oocyte or embryo, with low variance among technical replicates across a wide dynamic range of expression. These methods will not only be helpful for genomic and epigenetic research to identify regulatory mechanisms of early development and molecular signatures of embryo classes, but can also provide great potential for clinical analysis of small biopsy samples or pre-implantation genetic disease screening.
2012-01-06 | GSE26486 | GEO
Project description:MotivationMeasurement precision determines the power of any analysis to reliably identify significant signals, such as in screens for differential expression, independent of whether the experimental design incorporates replicates or not. With the compilation of large-scale RNA-Seq datasets with technical replicate samples, however, we can now, for the first time, perform a systematic analysis of the precision of expression level estimates from massively parallel sequencing technology. This then allows considerations for its improvement by computational or experimental means.ResultsWe report on a comprehensive study of target identification and measurement precision, including their dependence on transcript expression levels, read depth and other parameters. In particular, an impressive recall of 84% of the estimated true transcript population could be achieved with 331 million 50 bp reads, with diminishing returns from longer read lengths and even less gains from increased sequencing depths. Most of the measurement power (75%) is spent on only 7% of the known transcriptome, however, making less strongly expressed transcripts harder to measure. Consequently, <30% of all transcripts could be quantified reliably with a relative error<20%. Based on established tools, we then introduce a new approach for mapping and analysing sequencing reads that yields substantially improved performance in gene expression profiling, increasing the number of transcripts that can reliably be quantified to over 40%. Extrapolations to higher sequencing depths highlight the need for efficient complementary steps. In discussion we outline possible experimental and computational strategies for further improvements in quantification precision.Contactrnaseq10@boku.ac.at
| S-EPMC3117338 | biostudies-literature
Project description:Measuring the global gene expression pattern in a single cell has been technically challenging, but is potentially very useful for understanding variation in biological processes between cells and for studying gene regulation during early embryo development with single cell resolution. To advance these applications, multiple systems for single-cell RNA extraction in addition to crude cell lysis followed by RNA profiling were examined and used for genomic data analysis. Our results indicate that some of these methods are suitable for analyzing even a portion of the total RNA from a single oocyte or embryo, with low variance among technical replicates across a wide dynamic range of expression. These methods will not only be helpful for genomic and epigenetic research to identify regulatory mechanisms of early development and molecular signatures of embryo classes, but can also provide great potential for clinical analysis of small biopsy samples or pre-implantation genetic disease screening. RNA from single mouse oocytes was purified using Qiagen Rneasy Mini or Arcturus PicoPure kits. Crude lysates of single oocytes were also prepared in NuGEN direct lysis buffer. Three replicate oocytes for each of the three sample preparation methods were used. Total RNA was amplified by NuGEN Ovation One-Direct ribo-SPIA, cDNA products were biotinylated, and labeled targets were hybridized to Affymetrix Mouse Gene 1.0ST Arrays.
2012-01-06 | E-GEOD-26486 | biostudies-arrayexpress
Project description:BACKGROUND: Stevia (Stevia rebaudiana) is an important medicinal plant that yields diterpenoid steviol glycosides (SGs). SGs are currently used in the preparation of medicines, food products and neutraceuticals because of its sweetening property (zero calories and about 300 times sweeter than sugar). Recently, some progress has been made in understanding the biosynthesis of SGs in Stevia, but little is known about the molecular mechanisms underlying this process. Additionally, the genomics of Stevia, a non-model species, remains uncharacterized. The recent advent of RNA-Seq, a next generation sequencing technology, provides an opportunity to expand the identification of Stevia genes through in-depth transcript profiling. RESULTS: We present a comprehensive landscape of the transcriptome profiles of three genotypes of Stevia with divergent SG compositions characterized using RNA-seq. 191,590,282 high-quality reads were generated and then assembled into 171,837 transcripts with an average sequence length of 969 base pairs. A total of 80,160 unigenes were annotated, and 14,211 of the unique sequences were assigned to specific metabolic pathways by the Kyoto Encyclopedia of Genes and Genomes. Gene sequences of all enzymes known to be involved in SG synthesis were examined. A total of 143 UDP-glucosyltransferase (UGT) unigenes were identified, some of which might be involved in SG biosynthesis. The expression patterns of eight of these genes were further confirmed by RT-QPCR. CONCLUSION: RNA-seq analysis identified candidate genes encoding enzymes responsible for the biosynthesis of SGs in Stevia, a non-model plant without a reference genome. The transcriptome data from this study yielded new insights into the process of SG accumulation in Stevia. Our results demonstrate that RNA-Seq can be successfully used for gene identification and transcript profiling in a non-model species.
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Project description:We present SMURF-seq, a protocol to efficiently sequence short DNA molecules on a long-read sequencer by randomly ligating them to form long molecules. Applying SMURF-seq using the Oxford Nanopore MinION yields up to 30 fragments per read, providing an average of 6.2 and up to 7.5 million mappable fragments per run, increasing information throughput for read-counting applications. We apply SMURF-seq on the MinION to generate copy number profiles. A comparison with profiles from Illumina sequencing reveals that SMURF-seq attains similar accuracy. More broadly, SMURF-seq expands the utility of long-read sequencers for read-counting applications.
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Project description:Molecular changes occurring during mammalian oocyte maturation are partly regulated by cytoplasmic polyadenylation (CP) and affect oocyte quality, yet the extent of CP activity during oocyte maturation remains unknown. Single bovine oocyte RNA sequencing (RNA-Seq) was performed to examine changes in transcript abundance during in vitro oocyte maturation in cattle. Polyadenylated RNA from individual germinal-vesicle and metaphase-II oocytes was amplified and processed for Illumina sequencing, producing approximately 30 million reads per replicate for each sample type. A total of 10,494 genes were found to be expressed, of which 2,455 were differentially expressed (adjusted P < 0.05 and fold change >2) between stages, with 503 and 1,952 genes respectively increasing and decreasing in abundance. Differentially expressed genes with complete 3'-untranslated-region sequence (279 increasing and 918 decreasing in polyadenylated transcript abundance) were examined for the presence, position, and distribution of motifs mediating CP, revealing enrichment (85%) and lack thereof (18%) in up- and down-regulated genes, respectively. Examination of total and polyadenylated RNA abundance by quantitative PCR validated these RNA-Seq findings. The observed increases in polyadenylated transcript abundance within the RNA-Seq data are likely due to CP, providing novel insight into targeted transcripts and resultant differential gene expression profiles that contribute to oocyte maturation.
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