Fluidigm C1 + Illumina HiSeq quantitative whole transcriptome analysis of unsorted population of E16.5 lung cells
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE69761 | GEO | 2015/06/11
SECONDARY ACCESSION(S): PRJNA286698
REPOSITORIES: GEO
Similar Datasets
Project description:We used microfluidic single cell RNA-seq on mixed e16.5 mouse lung cells in order to determine the potential cell types present based on differential transcriptional profiles of the entire population using minimal cell selection bias. whole lung mouse e16.5 cells were pooled and loaded onto the Fluidigm C1 device. microwells that contained intact single cells were recorded, the labchip was processed for the generation of cDNA from each cell, and cDNA generated from each accepted well was used to generate amplified and barcoded DNA library that was loaded into an Iluumina HiSeq machine for HTS analysis.
2015-06-11 | E-GEOD-69761 | biostudies-arrayexpress
Project description:Purpose: Opium poppy is one of the most important medical plants and remains the only commercial resource of morphinan-based painkillers. However, little is known about its regulation mechanism in benzylisoquinoline alkaloids (BIAs) biosynthesis. Herein, the Transcriptome dataset of Opium poppy was constructed to identify the gene involved in its regulation mechanism in BIAs biosynthesis. Methods: Using Illumina HiSeq X Ten platform, 33 samples of Illumina transcriptome data from different tissues, growth phases and cultivars were constructed. Results: The high-quality transcripts were subsequent quantified with the short reads, and the expression of each unigenes among different samples was calculated by RPKM (the reads per kilobase per million mapped reads). Conclusions: These data provide a foundation of opium poppy transcriptome which may contribute to understand the regulation of BIAs biosynthesis.
2019-04-11 | GSE129567 | GEO
Project description:Purpose: Opium poppy is one of the most important medical plants and remains the only commercial resource of morphinan-based painkillers. However, little is known about its regulation mechanism in benzylisoquinoline alkaloids (BIAs) biosynthesis. Herein, the Transcriptome dataset of Opium poppy was constructed to identify the gene involved in its regulation mechanism in BIAs biosynthesis. Methods: Using Illumina HiSeq X Ten platform, 33 samples of Illumina transcriptome data from different tissues, growth phases and cultivars were constructed. Results: The high-quality transcripts were subsequent quantified with the short reads, and the expression of each unigenes among different samples was calculated by RPKM (the reads per kilobase per million mapped reads). Conclusions: These data provide a foundation of opium poppy transcriptome which may contribute to understand the regulation of BIAs biosynthesis.
2019-04-11 | GSE129566 | GEO
Project description:Purpose: Opium poppy is one of the most important medical plants and remains the only commercial resource of morphinan-based painkillers. However, little is known about its regulation mechanism in benzylisoquinoline alkaloids (BIAs) biosynthesis. Herein, the Transcriptome dataset of Opium poppy was constructed to identify the gene involved in its regulation mechanism in BIAs biosynthesis. Methods: Using Illumina HiSeq X Ten platform, 33 samples of Illumina transcriptome data from different tissues, growth phases and cultivars were constructed. Results: The high-quality transcripts were subsequent quantified with the short reads, and the expression of each unigenes among different samples was calculated by RPKM (the reads per kilobase per million mapped reads). Conclusions: These data provide a foundation of opium poppy transcriptome which may contribute to understand the regulation of BIAs biosynthesis.
2019-04-11 | GSE129565 | GEO
Project description:This study provides an assessment of the Fluidigm C1 platform for RNA sequencing of single mouse pancreatic islet cells. The system combines microfluidic technology and nanoliter-scale reactions. We sequenced 622 cells allowing identification of 341 islet cells with high-quality gene expression profiles. The cells clustered into populations of alpha-cells (5%), beta-cells (92%), delta-cells (1%) and PP-cells (2%). We identified cell-type specific transcription factors and pathways primarily involved in nutrient sensing and oxidation and cell signaling. Unexpectedly, 281 cells had to be removed from the analysis due to low viability (23%), low sequencing quality (13%) or contamination resulting in the detection of more than one islet hormone (64%). Collectively, we provide a resource for identification of high-quality gene expression datasets to help expand insights into genes and pathways characterizing islet cell types. We reveal limitations in the C1 Fluidigm cell capture process resulting in contaminated cells with altered gene expression patterns. This calls for caution when interpreting single-cell transcriptomics data using the C1 Fluidigm system. Single-cell RNA sequencing of mouse C57BL/6 pancreatic islet cells
2016-02-19 | E-GEOD-77980 | biostudies-arrayexpress
Project description:This study provides an assessment of the Fluidigm C1 platform for RNA sequencing of single mouse pancreatic islet cells. The system combines microfluidic technology and nanoliter-scale reactions. We sequenced 622 cells allowing identification of 341 islet cells with high-quality gene expression profiles. The cells clustered into populations of alpha-cells (5%), beta-cells (92%), delta-cells (1%) and PP-cells (2%). We identified cell-type specific transcription factors and pathways primarily involved in nutrient sensing and oxidation and cell signaling. Unexpectedly, 281 cells had to be removed from the analysis due to low viability (23%), low sequencing quality (13%) or contamination resulting in the detection of more than one islet hormone (64%). Collectively, we provide a resource for identification of high-quality gene expression datasets to help expand insights into genes and pathways characterizing islet cell types. We reveal limitations in the C1 Fluidigm cell capture process resulting in contaminated cells with altered gene expression patterns. This calls for caution when interpreting single-cell transcriptomics data using the C1 Fluidigm system.
2016-02-19 | GSE77980 | GEO
Project description:BackgroundDastarcus helophoroides is known as the most valuable natural enemy insect against many large-body longhorned beetles. The molecular mechanism of its long lifespan and reproduction makes it a unique resource for genomic research. However, molecular biological studies on this parasitic beetle are scarce, and genomic information for D. helophoroides is not currently available. Thus, transcriptome information for this species is an important resource that is required for a better understanding of the molecular mechanisms of D. helophoroides. In this study, we obtained transcriptome information of D. helophoroides using high-throughput RNA sequencing.ResultsUsing Illumina HiSeq 2000 sequencing, 27,543,746 clean reads corresponding to a total of 2.48 Gb nucleotides were obtained from a single run. These reads were assembled into 42,810 unigenes with a mean length of 683 bp. Using a sequence similarity search against the five public databases (NR, Swiss-Prot, GO, COG, KEGG) with a cut-off E-value of 10(-5) using Blastx, a total of 31,293 unigenes were annotated with gene description, gene ontology terms, or metabolic pathways.ConclusionsTo the best of our knowledge, this is the first study on the transcriptome information of D. helophoroides. The transcriptome data presented in this study provide comprehensive information for future studies in D. helophoroides, particularly for functional genomic studies in this parasitic beetle.
| S-EPMC4076278 | biostudies-literature
Project description:Methylation of cytosine in genomic DNA is a well-characterized epigenetic modification involved in many cellular processes and diseases. Whole-genome bisulfite sequencing (WGBS), such as MethylC-seq and post-bisulfite adaptor tagging sequencing (PBAT-seq), uses the power of high-throughput DNA sequencers and provides genome-wide DNA methylation profiles at single-base resolution. However, the accuracy and consistency of WGBS outputs in relation to the operating conditions of high-throughput sequencers have not been explored.We have used the Illumina HiSeq platform for our PBAT-based WGBS, and found that different versions of HiSeq Control Software (HCS) and Real-Time Analysis (RTA) installed on the system provided different global CpG methylation levels (approximately 5% overall difference) for the same libraries. This problem was reproduced multiple times with different WGBS libraries and likely to be associated with the low sequence diversity of bisulfite-converted DNA. We found that HCS was the major determinant in the observed differences. To determine which version of HCS is most suitable for WGBS, we used substrates with predetermined CpG methylation levels, and found that HCS v2.0.5 is the best among the examined versions. HCS v2.0.12 showed the poorest performance and provided artificially lower CpG methylation levels when 5-methylcytosine is read as guanine (first read of PBAT-seq and second read of MethylC-seq). In addition, paired-end sequencing of low diversity libraries using HCS v2.2.38 or the latest HCS v2.2.58 was greatly affected by cluster densities.Software updates in the Illumina HiSeq platform can affect the outputs from low-diversity sequencing libraries such as WGBS libraries. More recent versions are not necessarily the better, and HCS v2.0.5 is currently the best for WGBS among the examined HCS versions. Thus, together with other experimental conditions, special care has to be taken on this point when CpG methylation levels are to be compared between different samples by WGBS.
| S-EPMC5217569 | biostudies-literature
Project description:DNA sequencing continues to decrease in cost with the Illumina HiSeq2000 generating up to 600?Gb of paired-end 100 base reads in a ten-day run. Here we present a protocol for community amplicon sequencing on the HiSeq2000 and MiSeq Illumina platforms, and apply that protocol to sequence 24 microbial communities from host-associated and free-living environments. A critical question as more sequencing platforms become available is whether biological conclusions derived on one platform are consistent with what would be derived on a different platform. We show that the protocol developed for these instruments successfully recaptures known biological results, and additionally that biological conclusions are consistent across sequencing platforms (the HiSeq2000 versus the MiSeq) and across the sequenced regions of amplicons.
| S-EPMC3400413 | biostudies-literature
Project description:The Illumina HiSeq platform has been a commonly used option for bacterial genome sequencing. Now the BGI DNA nanoball (DNB) nanoarrays platform may provide an alternative platform for sequencing of bacterial genomes. To explore the impact of sequencing platforms on bacterial genome assembly, quality assessment, sequence alignment, functional annotation, mutation detection, and metagenome mapping, we compared genome assemblies based on sequencing of cultured bacterial species using the HiSeq 2000 and BGISEQ-500 platforms. In addition, simulated reads were used to evaluate the impact of insert size on genome assembly. Genome assemblies based on BGISEQ-500 sequencing exhibited higher completeness and fewer N bases in high GC genomes, whereas HiSeq 2000 assemblies exhibited higher N50. The majority of assembly assessment parameters, sequences of 16S rRNA genes and genomes, numbers of single nucleotide variants (SNV), and mapping to metagenome data did not differ significantly between platforms. More insertions were detected in HiSeq 2000 genome assemblies, whereas more deletions were detected in BGISEQ-500 genome assemblies. Insert size had no significant impact on genome assembly. Taken together, our results suggest that DNBSEQ platforms would be a valid substitute for HiSeq 2000 for bacterial genome sequencing.
| S-EPMC10788345 | biostudies-literature