Project description:N6-methyladnine, which is the most abundant post-transcriptional RNA modification in eukaryotic mRNA, has been proved to be essential in various biological processes and related to numerous diseases. Transcriptome-wide m6A profiling by next generation sequencing is widely used to explore the distributions as well as quantity of m6A modifications. As traditional m6A-seq demands large amount of starting RNA which limited its application to clinical samples, we present a strategy of low input multi-barcode m6A-seq (SLIM-m6A-seq) to realize simplified m6A profiling of mixed clinical samples. This method maintains the advantages of preferable detection limit, low cost and simplified experiment procedures. Sequencing data of clinical blood samples from patients with diabetic myocardial infarction suggest that this method is practical in clinical application and m6A may play a critical role in the progression of diabetic cardiovascular complications.
Project description:Deciphering epigenetic regulation of gene expression requires measuring the epigenome and transcriptome jointly. However, multi-omics profiling remains challenging for low-input samples. Therefore, we developed low-input ATAC&mRNA-Seq, a simple and robust method for studying the role of chromatin structure in gene regulation in a single experiment with thousands of cells, to maximize insights from limited input material by obtaining ATAC-seq and mRNA-seq data simultaneously from the same cells with data quality comparable to conventional mono-omics assays. Remarkably, integrative data analysis revealed similar strong association between promoter accessibility and gene expression using the data of low-input ATAC&mRNA-Seq as using single-assayed data, underscoring the accuracy and reliability of our dual-omics assay to generate both data types simultaneously with just thousands of cells. We envision our method to be widely applied in many biological disciplines with limited materials.
Project description:LiBis is a novel method for low-input WGBS data alignment. By dynamically clipping initially unmapped reads and remapping clipped fragments, we judiciously rescued those reads and uniquely aligned them to the genome. By substantially increasing the mapping ratio by up to 88%, LiBis improves the number of informative CpGs and the precision to quantify the methylation status of individual CpG sites. The high sensitivity and cost effectiveness afforded by LiBis for low-input samples will allow the discovery of genetic and epigenetic features suitable for downstream analysis and biomarker identification using liquid biopsy.
Project description:Here, we report the development and application of smartSHAPE, a SHAPE-like RNA structure probing method that requires low amounts of input due to the largely reduced artefact signals of premature RT stops and increased efficiency of library construction. We used smartSHAPE to profile the global RNA secondary structures of two subtypes of mouse colonic macrophages upon inflammation, and provided evidence that RNA conformational changes at protein binding sites regulate gene expression and, in turn, immune responses. We predicted functional RNA structure elements based on smartSHAPE structure data, and discovered that PD-L1 contains a YRY-motif stem-loop structural element within the 3’UTR, which triggers RNA degradation mediated by Regnase-1.
Project description:We developed a new method on sequencing low-input RNA. This method shows much low-bias with the advantage of semiconductor while competing with smart-seq2. In order to analyze the low-input RNA datasets sensitively, we also develop FANSe2splice with high experimental verification rate as the analysis tool in our method.
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.
Project description:We developed a sample preparation method for low-input proteomics using lauryl maltose neopentyl glycol. Using the developed method, we performed proteome analysis of coIP samples.