Fifty six genes from DESeq were differentially expressed in the treated versus control samples. More than 20% were related to immune, defense, wounding and inflammatory responses Overall design: Downregulation of REST-003 using siRNAs in MDA-MB-231 cells; we used siRNA against REST-003, as REST-003 may control invasiveness. We transfected si-Control (scramble) or si-REST-003 in MDA-MB-231: duplicate of both (total 4 samples).
Non-coding RNAs derived from an alternatively spliced REST transcript (REST-003) regulate breast cancer invasiveness.
No sample metadata fields
View SamplesWe conducted a large-scale control experiment to assess the transfer function of three scRNA-seq methods and factors modulating the function. Our approach was to dilute bulk total RNA (from a single source) to levels bracketing single-cell levels of total RNA (10 pg and 100 pg) in replicates and amplifying the RNA to levels sufficient for RNA sequencing. Overall design: We performed replicate transcriptome amplifications of Universal Human Reference RNA (UHR) and Human Brain Reference RNA (HBR) that were diluted to single-cell and ten-cell abundances (10 and 100 picograms (pg.) total RNA or ~200,000 and 2 million mRNA molecules, respectively) and were amplified using three single-cell RNA amplification methods. Methods included the antisense RNA IVT protocol (aRNA), a custom C1 SMARTer protocol (SmartSeq Plus) performed on a Fluidigm C1 96-well chip, and a modified NuGen Ovation RNA sequencing protocol (NuGen). Bulk ribo-depleted UHR and HBR RNA were sequenced and served as a reference. The general experimental scheme was consistent for all dilution replicates; however, there were differences across experimental groups in the specifics of experimental protocols, necessitated by particular methodologies. Because of these experimental differences, head-to-head comparison of methods is not appropriate and our goal is to provide quantitative analyses of factors affecting individual methods. Current results should be used in experimental planning, data analysis, and method optimization rather than as a performance test of any particular method. Detailed experimental design: Each collaborating center obtained reference RNA with the same lot number for Universal Human Reference (UHR) RNA (Agilent 740000, Lot 0006141415) and Human Brain Reference (HBR) (Ambion AM6050, Lot-105P055201A) and performed replicate amplification using a single amplification method, detailed below. SmartSeq Plus: Reference RNA was diluted to an intermediate stock solution by serial dilution. A final 1000-fold dilution occurred on the C1 chip, such that individual wells in a given batch contained 9.99 pg. sampled from a common intermediate dilution. ERCC spike-in RNA mix 1 (Ambion 4456740) was also added for a final mass of approximately 7 femtograms (fg.) per sample, a 4,000,000x dilution from stock. Samples for each source RNA were prepared in single batches. After amplification, cDNA from the entire C1 96-well plate was quantified using picogreen. C1 chips with an average yield of less than 3 nanograms were discarded. The top 15 reactor wells by cDNA concentration were selected as representative 10 pg. samples for sequencing library preparation. Another 50 wells were selected by the same criteria. These were pooled in sets of 10, generating 5 100 pg. samples for each HBR and UHR. All samples for a given source were prepared in a single sequencing library preparation batch using Nextera XT C1 protocol. NuGen: HBR samples were prepared in a single batch using amplification protocol 1, generating 4 10 pg. and 4 100 pg. amplified replicates. UHR samples were prepared in two batches, using either amplification protocol 1 or 2, generating 15 10 pg. and 11 100 pg. samples. A single sequencing library preparation was performed for each batch of samples using either Lucigen NxSeq or NuGen Ovation Rapid protocol. aRNA: Amplification was performed as previously described (Morris J, Singh JM, Eberwine JH. Transcriptome analysis of single cells. J. Vis. Exp. [Internet]. 2011; Available from: http://www.jove.com/video/2634/transcriptome-analysis-of-single-cells). HBR samples were prepared in 4 batches from separate dilutions of reference RNA, generating 19 10 pg. and 3 100 pg. amplified replicates. ERCC spike-ins were added to 5 of the 10 pg. replicates before amplification at a dilution of 4,000,000x from stock. UHR samples were diluted and amplified in 2 batches from separate dilutions of reference RNA, generating 12 10 pg. and 7 100 pg. amplified replicates. A single sequencing library preparation was performed using Illumina TruSeq Stranded mRNA protocol modified to begin with amplified aRNA. A small numbers of reads were assigned to ERCC transcripts in replicates from the batch where ERCCs had been added that did not have spike-ins added (average of 0.5% of the number of reads assigned in spiked samples). 18 additional HBR 10 pg. replicates were amplified using aRNA for protocol optimization experiments. These samples were treated separately and were excluded from primary analysis. Bulk UHR and HBR: For each reference RNA, three sequencing libraries were generated from bulk material at the same laboratory as the SmartSeq Plus replicates. Cytoplasmic and mitochondrial ribosomal RNA (rRNA) were depleted using Ribo-Zero Gold as part of Illumina TruSeq Stranded Total RNA protocol. Samples were sequenced on Illumina HiSeq 2000. Because of differences in experimental design, direct comparison across methods of precision and the effect of input RNA abundance is difficult. For example, input RNA amount as a factor have different meanings for the different amplification methods: for SmartSeq Plus, because 100pg samples were constructed by pooling 10 pg. samples after cDNA amplification, any resulting effects involve library construction, while for aRNA and NuGen resulting effects reflect both cDNA amplification steps and library steps.
Assessing characteristics of RNA amplification methods for single cell RNA sequencing.
Subject
View SamplesThe non-coding Xist RNA triggers silencing of one of the two female X chromosomes during X inactivation in mammals. Gene silencing by Xist is restricted to special developmental contexts found in cells of the early embryo and specific hematopoietic precursors. The absence of critical silencing factors might explain why Xist cannot silence outside these contexts. Here, we show that Xist can also initiate silencing in a lymphoma model. Using the tumor context we identify the special AT rich binding protein SATB1 as an essential silencing factor. We show that loss of SATB1 in tumor cells abrogates the silencing function of Xist. In normal female lymphocytes Xist localizes along SATB1 filaments and, importantly, forced Xist expression can relocalize SATB1 into the Xist cluster. This reciprocal influence on localization suggests a molecular interaction between Xist and SATB1. SATB1 and its close homologue SATB2 are expressed during the initiation window for X inactivation in embryonic stem cells and are recruited to surround the Xist cluster. Furthermore, ectopic expression SATB1 or SATB2 enables gene silencing by Xist in embryonic fibroblasts, which normally do not provide an initiation context. Thus, SATB1 functions as a crucial initiation factor and may act to organize genes for silencing by Xist during the initiation of X inactivation.
SATB1 defines the developmental context for gene silencing by Xist in lymphoma and embryonic cells.
Specimen part
View SamplesThe overall aim of this experiment was to identify specific genes and molecular pathways regulated by ML290, a small molecule agonist of the relaxin receptor, RXFP1, in the context of liver fibrosis. Overall design: Whole transcriptome mRNA sequencing of transformed LX-2 cells using HiSeq platforms with paired-end 150 bp (PE 150) sequencing strategy, with four biological replicates in each treatment group.
Therapeutic effects of a small molecule agonist of the relaxin receptor ML290 in liver fibrosis.
Specimen part, Cell line, Subject
View SamplesOne of the major players controlling RNA decay is the cytoplasmic 5'-to-3' exoribonuclease, which is conserved among eukaryotic organisms. In Arabidopsis, the 5'-to-3' exoribonuclease XRN4 is involved in disease resistance, the response to ethylene, RNAi, and miRNA-mediated RNA decay. Curiously, XRN4 appears to display selectivity among its substrates because certain 3' cleavage products formed by miRNA-mediated decay, such as from ARF10 mRNA, accumulate in the xrn4 mutant, whereas others, such as from AGO1, do not. To examine the nature of this selectivity, transcripts that differentially accumulate in xrn4 were identified by combining PARE and Affymetrix arrays. Certain functional categories, such as stamen-associated proteins and hydrolases, were over-represented among transcripts decreased in xrn4, whereas transcripts encoding nuclear-encoded chloroplast-targeted proteins and nucleic acid-binding proteins were over-represented in transcripts increased in xrn4. To ascertain if RNA sequence influences the apparent XRN4 selectivity, a series of chimeric constructs was generated in which the miRNA-complementary sites and different portions of the surrounding sequences from AGO1 and ARF10 were interchanged. Analysis of the resulting transgenic plants revealed that the presence of a 150 nucleotide sequence downstream from the ARF10 miRNA-complementary site conferred strong accumulation of the 3' cleavage products in xrn4. In addition, sequence analysis of differentially accumulating transcripts led to the identification of 27 hexamer motifs that were over-represented in transcripts or miRNA-cleavage products accumulating in xrn4. Taken together, the data indicate that specific mRNA sequences, like those in ARF10, and mRNAs from select functional categories are attractive targets for XRN4-mediated decay.
Evidence that XRN4, an Arabidopsis homolog of exoribonuclease XRN1, preferentially impacts transcripts with certain sequences or in particular functional categories.
Specimen part
View SamplesCertain neuron types fire spontaneously at high rates, an ability that is crucial for their function in brain circuits. The spontaneously active GABAergic neurons of the substantia nigra pars reticulata (SNr), a major output of the basal ganglia, provide tonic inhibition of downstream brain areas. A depolarizing "leak" current supports this firing pattern, but its molecular basis remains poorly understood. To understand how SNr neurons maintain tonic activity, we used single-cell RNA sequencing to determine the transcriptome of individual SNr neurons. We discovered that SNr neurons express the sodium leak current, NaLCN and that SNr neurons lacking NaLCN have impaired spontaneous firing. Overall design: RNA sequencing profiles from 87 GFP-positive GABAergic SNr neurons and 9 GFP-negative SNr cells were carried out. However only 80 samples that passed initial quality control and that were included in the data processing are represented in this record.
The leak channel NALCN controls tonic firing and glycolytic sensitivity of substantia nigra pars reticulata neurons.
Specimen part, Cell line, Subject
View SamplesThis SuperSeries is composed of the SubSeries listed below.
Identification of artifactual microarray probe signals constantly present in multiple sample types.
Specimen part
View SamplesThe correlation of the RNA profiles obtained by microarray analysis was compared with that obtained from RNA-Seq by using reduced complexity sperm datasets. This resolved as a series of discordant probes. The extent of discordancy among other datasets was then determined.
Identification of artifactual microarray probe signals constantly present in multiple sample types.
Specimen part
View SamplesTranscriptome analysis of depletion of DYRK1A in HeLa cells
DYRK1A phoshorylates histone H3 to differentially regulate the binding of HP1 isoforms and antagonize HP1-mediated transcriptional repression.
Specimen part, Cell line
View SamplesThe correlation of the RNA profiles obtained by microarray analysis was compared with that obtained from RNA-Seq by using reduced complexity sperm datasets. This resolved as a series of discordant probes. The extent of discordancy among other datasets was then determined. Overall design: A correlative study between probe’s signal intensity from Illumina bead arrays with its transcript level detected by next generation sequencing technique was performed. RNAs from sperm and testis samples were applied
Identification of artifactual microarray probe signals constantly present in multiple sample types.
Specimen part, Subject
View Samples