Establishment of Transposase-assisted Low-input m6A Sequencing Technique
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ABSTRACT:
PROVIDER: PRJNA704264 | ENA |
REPOSITORIES: ENA
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Project description:As the most abundant and best-characterized internal mRNA modification, N6-methyladenosine (m6A) emerges to play a critical regulatory role in wide range of physiological and pathological processes, including gametogenesis, neuronal development, obesity and tumorigenesis. Methylated RNA immunoprecipitation coupled with next-generation sequencing (MeRIP-seq) facilitates transcriptome-wide m6A profiling, also is the most widely used technique to understand the biological significance of m6A. However, it typically requires over 100 μg of total RNA or 107 cells as input materials, hampering its application in limited samples. Here, we develop tMeRIP-seq, a transposase assisted MeRIP-seq method to achieve m6A profiling using ultra-low amount of input RNA. By marrying Tn5 tagmentation to m6A-specific immunoprecipitation, tMeRIP-seq largely improves the efficiency of library construction and reduces the input materials to as little as 60 ng total RNA or 103 cells. We apply this method on a small droplet of human blood and recapitulate the m6A profile previously reported using conventional protocol. We find tMeRIP-seq is a convenient and powerful method to examine m6A in ultra-low input material, potentially providing m6A as a new layer of bio-marker for liquid biopsy.
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Project description:Transposase assisted tagmentation of RNA/DNA hybrid duplexes
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Project description:Deep sequencing of single cell-derived genomic DNA and/or cDNAs brings novel insights into oncogenesis and embryogenesis. However, traditional library preparation for RNA-Seq requires multiple steps, including shearing the target DNA/RNA and following sequential enzymatic reactions, which result in consequent sample loss and stochastic variation at each step. Such variation may significantly affect the output from sequencing. We have found that a new technique of library preparation using hyperactive Tn5 transposase for the next-generation sequencer of Illumina's platform provided high-quality libraries from 100ng of short-length (average 700~800 bp) single-cell level cDNA. This new method reduced the number of steps in the protocol, which resulted in improved reproducibility and reduced variation among the specimens. Two methods of library preparation (sonication, tagmentation with hyperactive Tn5 transposase) were compared in the case of RNA-Seq for single-cell level cDNA. Technical triplicates were used.
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Project description:We report evolved TadA-assisted N6-methyladenosine sequencing (eTAM-seq), an enzyme-assisted sequencing technology for quantitative, base-resolution profiling of m6A. eTAM-seq functions by global adenosine deamination, enabling detection of m6A as persistent A. We demonstrate adenosine-to-inosine (I) conversion rates up to 99% using a hyperactive TadA variant. With eTAM-seq, we profile and quantify m6A in the whole transcriptomes of HeLa cells and mouse embryonic stem cells (mESCs), with simultaneous deconvolution of the transcriptome and epitranscriptome. Further, we showcase deep sequencing-free, site-specific m6A quantification with as few as 10 cells, an input demand that is at least 4 orders of magnitude lower than existing methods. Collectively, eTAM-seq enables sensitive detection and faithful quantification of m6A with limited RNA input, representing a novel solution to deciphering the epitranscriptome.
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Project description:We report evolved TadA-assisted N6-methyladenosine sequencing (eTAM-seq), an enzyme-assisted sequencing technology for quantitative, base-resolution profiling of m6A. eTAM-seq functions by global adenosine deamination, enabling detection of m6A as persistent A. We demonstrate adenosine-to-inosine (I) conversion rates up to 99% using a hyperactive TadA variant. With eTAM-seq, we profile and quantify m6A in the whole transcriptomes of HeLa cells and mouse embryonic stem cells (mESCs), with simultaneous deconvolution of the transcriptome and epitranscriptome. Further, we showcase deep sequencing-free, site-specific m6A quantification with as few as 10 cells, an input demand that is at least 4 orders of magnitude lower than existing methods. Collectively, eTAM-seq enables sensitive detection and faithful quantification of m6A with limited RNA input, representing a novel solution to deciphering the epitranscriptome.
2022-10-24 | GSE201062 | GEO