Sensitive and reproducible cell-free methylome quantification with synthetic spike-in controls
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PROVIDER: EGAS00001005069 | EGA |
REPOSITORIES: EGA
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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:Synthetic spike-in controls enable sensitive and reproducible cell-free methylome interrogation
| PRJNA699882 | ENA
Project description:We created three technical replicates of cell-free DNA from AML patient plasma to assess batch effects and utility of spike-in controls for the cfMeDIP-seq method. Each set of samples were given to three different technicians with slightly different protocols. Details can be found in Wilson et al. "Sensitive and reproducible cell-free methylome quantification with synthetic spike-in controls".
| EGAD00001006986 | EGA
Project description:Recently, next-generation sequencing has been introduced as a promising, new platform for assessing the copy number of transcripts, while the existing microarray technology is considered less reliable for absolute, quantitative expression measurements. Nonetheless, so far, results from the two technologies have only been compared based on biological data, leading to the conclusion that, although they are somewhat correlated, expression values differ significantly. Here, we use synthetic RNA samples, resembling human microRNA samples, to find that microarray expression measures actually correlate better with sample RNA content than expression measures obtained from sequencing data. In addition, microarrays appear highly sensitive and perform equivalently to next-generation sequencing in terms of reproducibility and relative ratio quantification.
2009-09-08 | GSE14511 | GEO
Project description:Three separate experiments were carried out using MeDIP-seq and cfMeDIP-seq for methylome analysis. For the first experiment, different starting amounts of HCT116 cell line DNA, sheared to mimic cell-free DNA, were analyzed using MeDIP-seq and cfMeDIP-seq. In the second experiment the limit of detection of cfMeDIP-seq was tested using varying dilutions of colorectal cancer cell line DNA (HCT116) with multiple myeloma cell line DNA (MM1.S). For both cell line DNA samples, the DNA was sheared to mimic cell-free DNA. In the final experiment, we tested the enrichment of human ctDNA using cfMeDIP-seq performed on plasma collected from patient-derived xenografts (PDXs) generated in mice from two colorectal cancer patients.
2018-04-01 | GSE79838 | GEO
Project description:Time course of batch growth. Reference (channel 1) was a culture grown in MD medium with 2.4 g/L glucose, with 5 slpm air-flow, stirring at 400 rpm and a constant 300C temperature, dilution 0.25 volumes/hour. The experimental (channel 2) time course samples were grown in batch for the indicated time. The "Low-D chemostat vs. High-D chemostat" hybridization's channel 2 sample was grown in a chemostat, with a dilution rate of 0.05 volumes/hour; it is most similar to the time course samples taken between 8 and 9 hours. Groups of assays that are related as part of a time series. FactorCategory: Elapsed Time; name: Elapsed Time; Measurement: time(absolute) 0 h; name: 45181_Elapsed Time; Measurement: time(absolute) 8.5 h; name: 38150_Elapsed Time; Measurement: time(absolute) 8.75 h; name: 38151_Elapsed Time; Measurement: time(absolute) 9 h; name: 38152_Elapsed Time; Measurement: time(absolute) 9.25 h; name: 38153_Elapsed Time; Measurement: time(absolute) 7.25 h; name: 38145_Elapsed Time; Measurement: time(absolute) 9.5 h; name: 38154_Elapsed Time; Measurement: time(absolute) 7.5 h; name: 38146_Elapsed Time; Measurement: time(absolute) 9.75 h; name: 38155_Elapsed Time; Measurement: time(absolute) 7.75 h; name: 38147_Elapsed Time; Measurement: time(absolute) 10 h; name: 38156_Elapsed Time; Measurement: time(absolute) 8 h; name: 38148_Elapsed Time; Measurement: time(absolute) 8.25 h; name: 38149_Elapsed Time FactorCategory: Growth Condition; name: Growth Condition; Growth Condition: chemostat dilution control; name: 45181_Growth Condition; Growth Condition: batch; name: 38150_Growth Condition; Growth Condition: batch; name: 38151_Growth Condition; Growth Condition: batch; name: 38152_Growth Condition; Growth Condition: batch; name: 38153_Growth Condition; Growth Condition: batch; name: 38145_Growth Condition; Growth Condition: batch; name: 38154_Growth Condition; Growth Condition: batch; name: 38146_Growth Condition; Growth Condition: batch; name: 38155_Growth Condition; Growth Condition: batch; name: 38147_Growth Condition; Growth Condition: batch; name: 38156_Growth Condition; Growth Condition: batch; name: 38148_Growth Condition; Growth Condition: batch; name: 38149_Growth Condition Keywords: time_series_design
2005-08-26 | GSE3205 | GEO
Project description:MicroRNAs (miRNAs) have been shown to play an important role in many different cellular, developmental, and physiological processes. Accordingly, numerous methods have been established to identify and quantify miRNAs. The shortness of miRNA sequence results in a high dynamic range of melting temperatures and, moreover, impedes a proper selection of detection probes or optimized PCR primers. While miRNA microarrays allow for massive parallel and accurate relative measurement of all known miRNAs, they have so far been less useful as an assay for absolute quantification. Here, we present a microarray based approach for global and absolute quantification of miRNAs. The method relies on an equimolar pool of about 1000 synthetic miRNAs of known concentration which is used as an universal reference and labeled and hybridized in a dual colour approach on the same array as the sample of interest. Each single miRNA is quantified with respect to the universal reference outbalancing bias related to sequence, labeling, hybridization or signal detection method. We demonstrate the accuracy of the method by various spike in experiments. Further, we quantified miRNA copy numbers in liver samples and CD34(+)CD133(-) hematopoietic stem cells.
2009-10-27 | GSE15835 | GEO
Project description:Absolute quantification of miRNAs
| PRJNA116765 | ENA
Project description:SIRVs: Spike-In RNA Variants as External Isoform Controls in RNA-Sequencing
| PRJNA312485 | ENA
Project description:MicroRNAs (miRNAs) have been shown to play an important role in many different cellular, developmental, and physiological processes. Accordingly, numerous methods have been established to identify and quantify miRNAs. The shortness of miRNA sequence results in a high dynamic range of melting temperatures and, moreover, impedes a proper selection of detection probes or optimized PCR primers. While miRNA microarrays allow for massive parallel and accurate relative measurement of all known miRNAs, they have so far been less useful as an assay for absolute quantification. Here, we present a microarray based approach for global and absolute quantification of miRNAs. The method relies on an equimolar pool of about 1000 synthetic miRNAs of known concentration which is used as an universal reference and labeled and hybridized in a dual colour approach on the same array as the sample of interest. Each single miRNA is quantified with respect to the universal reference outbalancing bias related to sequence, labeling, hybridization or signal detection method. We demonstrate the accuracy of the method by various spike in experiments. Further, we quantified miRNA copy numbers in liver samples and CD34(+)CD133(-) hematopoietic stem cells. Total liver RNA was mixed with 2.5 fmol of each of 18 RNA oligonucleotides reverse complement to miRControl 3 probes and subsequently fluorescently labelled by 3â ligation. Total RNA mix was hybridized in a dual colour approach to microarrays versus a second labelled synthetic miRNA pool (n = 6). The synthetic miRNA pool consisted of 2.5 fmol of each of 891 non redundant miRNAs sequences and miRControl 3 sequences. The array data was normalized by calculating the median of the miRControl 3 present in the liver and UR sample. The miRNA amount was calculated with respect to the corresponding miRNA in the UR.
2010-06-20 | E-GEOD-15835 | biostudies-arrayexpress