SiqRNA-seq is a spike-in-independent technique for quantitative mapping of mRNA landscape
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE223145 | GEO | 2024/04/08
REPOSITORIES: GEO
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Project description:Normalization of high-throughput small RNA sequencing (sRNA-Seq) data is required to compare sRNA levels across different samples. Commonly used relative normalization approaches can cause erroneous conclusions due to fluctuating small RNA populations between tissues. We developed a set of sRNA spike-in oligonucleotides (sRNA spike-ins) that enable absolute normalization of sRNA-Seq data across independent experiments, as well as the genome-wide estimation of sRNA:mRNA stoichiometries when used together with mRNA spike-in oligonucleotides.
2017-07-19 | GSE98553 | GEO
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2023-05-09 | GSE218644 | GEO
Project description:While the importance of random sequencing errors decreases at higher DNA or RNA sequencing depths, systematic sequencing errors (SSEs) dominate at high sequencing depths and can be difficult to distinguish from biological variants. These SSEs can cause base quality scores to underestimate the probability of error at certain genomic positions, resulting in false positive variant calls, particularly in mixtures such as samples with RNA editing, tumors, circulating tumor cells, bacteria, mitochondrial heteroplasmy, or pooled DNA. Most algorithms proposed for correction of SSEs require a training data set, which is typically either from a part of the data set being “recalibrated” (Genome Analysis ToolKit, or GATK) or from a separate data set with special characteristics (SysCall). Here, we combine the advantages of these approaches by adding synthetic RNA spike-in standards to human RNA, and use GATK to recalibrate base quality scores with reads mapped to the spike-in standards. Compared to conventional GATK recalibration that uses reads mapped to the genome, spike-ins improve the accuracy of Illumina base quality scores by a mean of 5 units, and by as much as 13 units at CpG sites. In addition, since reads mapping to the genome are not used for recalibration, our method allows run-specific recalibration even for the many species without a comprehensive and accurate SNP database. We also use GATK with the spike-in standards to demonstrate that the Illumina RNA sequencing runs overestimate quality scores for AC, CC, GC, GG, and TC dinucleotides, while SOLiD has less dinucleotide SSEs but more SSEs for certain cycles. We conclude that using these DNA and RNA spike-in standards with GATK improves base quality score recalibration.
2012-03-03 | GSE36217 | GEO
Project description:While the importance of random sequencing errors decreases at higher DNA or RNA sequencing depths, systematic sequencing errors (SSEs) dominate at high sequencing depths and can be difficult to distinguish from biological variants. These SSEs can cause base quality scores to underestimate the probability of error at certain genomic positions, resulting in false positive variant calls, particularly in mixtures such as samples with RNA editing, tumors, circulating tumor cells, bacteria, mitochondrial heteroplasmy, or pooled DNA. Most algorithms proposed for correction of SSEs require a training data set, which is typically either from a part of the data set being M-bM-^@M-^\recalibratedM-bM-^@M-^] (Genome Analysis ToolKit, or GATK) or from a separate data set with special characteristics (SysCall). Here, we combine the advantages of these approaches by adding synthetic RNA spike-in standards to human RNA, and use GATK to recalibrate base quality scores with reads mapped to the spike-in standards. Compared to conventional GATK recalibration that uses reads mapped to the genome, spike-ins improve the accuracy of Illumina base quality scores by a mean of 5 units, and by as much as 13 units M-BM- at CpG sites. In addition, since reads mapping to the genome are not used for recalibration, our method allows run-specific recalibration even for the many species without a comprehensive and accurate SNP database. We also use GATK with the spike-in standards to demonstrate that the Illumina RNA sequencing runs overestimate quality scores for AC, CC, GC, GG, and TC dinucleotides, while SOLiD has less dinucleotide SSEs but more SSEs for certain cycles. We conclude that using these DNA and RNA spike-in standards with GATK improves base quality score recalibration. Four human RNA samples with equimolar ERCC spike-in standards were sequenced on Illumina. Two human brain/liver/muscle RNA mixtures with dynamic range of ERCC spike-in standards were sequenced on SOLiD.
2012-03-03 | E-GEOD-36217 | biostudies-arrayexpress
Project description:Here we report on an RNAseq method in combination with spike-in cells to measure global changes in the transcription pattern after valine-induced isoleucine starvation of a standard E. coli K12 strain. Due to the spike-in method we were able to show that ribosomal RNA is degraded during isoleucine starvation and we showed how this change in cellular RNA content affect the estimated regulation of mRNA levels compared to if spike-in were not utilized. Our analysis also showed that induction of starvation by sudden addition of high valine concentrations provoked prominent regulatory responses outside of the expected ppGpp, RpoS and Lrp regulons
2019-11-19 | GSE136753 | GEO
Project description:In this study, we assess technical differences between commonly used single-cell RNA-Sequencing (scRNA-Seq) methods. We perform scRNA-seq on a homogenous population of mouse embryonic stem cells along with two kinds of control spike-in molecules to assess sensitivity and accuracy of these specific methods. In this dataset, we assess the RNA-degradation and decay rates by subjecting both spike-in molecules to range of repeated freezing and thawing (freeze-thaw) cycles. We manually add spike-in molecules across a 96-well plate (containing cells and reagents), perform Smart-Seq2 method manually and generate single-cell libraries using Nextera XT kit
2017-03-14 | E-MTAB-5481 | biostudies-arrayexpress
Project description:We have generated a wholly defined spike-in dataset for Agilent microarrays consisting of 12 arrays with more than 2000 differentially expressed, and approximately 3600 background, cRNAs. The composition of this “Ag Spike”dataset is identical to that of our previous Platinum Spike dataset (GSE21344) and therefore allows direct cross-platform comparison. Comparison between the Ag Spike and Platinum Spike studies shows high agreement between results obtained using the Affymetrix and Agilent platforms.
2010-10-23 | GSE24866 | GEO
Project description:Background.The cell-free methylated DNA immunoprecipitation-sequencing (cfMeDIP-seq) method, is adapted to work with low input DNA and with circulating cell-free DNA (cfDNA). This method allowsfor epigenetic profiling from liquid biopsy samples, providing potential information about tissue of origin. Similar to classical immunoprecipitation based enrichment protocols, interpretation requires a referenceor control to draw inference against a composite experimental baseline and against designed standards allowing for cross-experiment comparisons. Methods.To meet the need for a reference control in cfMeDIP-seqexperiments, we designed spike-in controlsand integrated the use of unique molecular index (UMI) to adjust for polymerase chain reaction (PCR)bias, and immunoprecipitation bias caused by the fragment length, G+C content, and CpG density ofthe DNA fragments. This enables for absolute quantification of methylated DNA in picomoles, while retaining epigenomic information that allows for sensitive, tissue-specific detection as well as comparableresults between different experiments. We designed 54 DNA fragments with combinations of methylationstatus (methylated and unmethylated), fragment length in base pair (bp) (80 bp,160 bp,320 bp), G+C content (35%,50%,65%), and fraction of CpGs within a fragment (1/80 bp,1/40 bp,1/20 bp). We checked spike-in control DNA sequence to ensure they had no cross alignment to the human genome and minimized formation of secondary structures to avoid issues with amplification. We carried outcfMeDIP-seq on either solely spike-in DNA fragments, spike-in DNA added to sheared HCT116 genomic DNA or spike-inDNA added tocfDNAfrom acute myeloid leukemia (AML) samples to assess technical and biological biases, determine optimal amount of spike-in DNA required for an experiment and to assess batch effects,respectively. Results. We show thatcfMeDIP-seqenriches for highly methylated regions, with less than 0.01%non-specific binding and preference to high G+C content and CpG fraction DNA fragments. The use of 0.01 ngof spike-in control DNA results in sufficient sequencing reads to adjust for variance due to fragment length,G+C content and CpG fraction without negatively impacting the number of sequencing reads generatedfor each sample. With known amount of each spike-in control, we generated a generalized linear modelthat can absolutely quantify molar amount from read counts while adjusting for fragment length, G+C content, and CpG fraction. Using our spike-in controls, we show that we can greatly mitigate batch effects,reducing batch associated variance in the data to ≤5%of the total variance. Conclusions.The incorporation of spike-in controls allows for easier interpretation of data generated from cfMeDIP-seq and MeDIP-seq experiments when compared to relative read count. Through the use of a generalized linear model tailored to each experiment, molar amount for each genomic region can becalculated, greatly mitigating both biological and technical biases in the data. We have created an Rpackage, spiky, to convert read counts to DNA picomoles while adjusting for fragment length, G+C contentand CpG fraction.
2021-02-16 | GSE166259 | GEO
Project description:Mass spectrometry remains an important method for analysis of modified nucleosides ubiquitously present in cellular RNAs, in particular for ribosomal and transfer RNAs that play crucial roles in mRNA translation and decoding. Furthermore, modifications have effect on the lifetimes of nucleic acids in plasma and cells and are consequently incorporated into RNA therapeutics. To provide an analytical tool for sequence characterization of modified RNAs, we developed Pytheas, an open-source software package for automated analysis of tandem MS data for RNA. This dataset contains the analysis of 14N and 15N-labeled synthetic mRNA of the SARS-CoV-2 spike protein. All uridines were modified to m1Ψ.
2022-05-04 | PXD030845 | Pride
Project description:mRNA vaccination of individuals with prior SARS-CoV-2 infection provides superior protection against breakthrough infections with variants of concern compared to vaccination in the absence of prior infection. However, the immune mechanisms by which this ‘hybrid immunity’ is generated and maintained are unknown. While genetic variation in spike glycoprotein effectively subverts neutralizing antibodies, spike-specific T cells are generally maintained against SARS-CoV-2 variants. Thus, we comprehensively profiled T cell responses against the S1 and S2 domains of spike glycoprotein in a cohort of SARS-CoV-2-naive or convalescent individuals who received two-dose mRNA vaccine series and were matched by age, sex, and vaccine type. Using flow cytometry, we observed that the overall functional breadth of CD4 T cells as well as polyfunctional Th1 responses were similar between the two groups. However, polyfunctional cytotoxic CD4 T cell responses against both S1 and S2 domains trended higher among convalescent subjects. Multi-modal single-cell RNA sequencing revealed diverse functional programs in spike-specific CD4 and CD8 T cells in both groups. However, convalescent individuals displayed enhanced cytotoxic and antiviral CD8 T cell responses to both S1 and S2 in the absence of cytokine production. Taken together, our data suggest that cytotoxic CD4 and CD8 T cells targeting spike glycoprotein may partially account for hybrid immunity and protection against breakthrough infections with SARS-CoV-2.
2023-03-01 | GSE223236 | GEO