Biology subjects

Murugan, V.

Publications and source records attributed to Murugan, V..

2 recordsLinked to original sources

bioRxiv2024

CountASAP: A Lightweight, Easy to Use Python Package for Processing ASAPseq Data

Declining sequencing costs coupled with the increasing availability of easy-to-use kits for the isolation of DNA and RNA transcripts from single cells have driven a rapid proliferation of studies centered around genomic and transcriptomic data. Simultaneously, a wealth of new techniques have been developed that utilize single cell technologies to interrogate a broad range of cell-biological processes. One recently developed technique, transposase-accessible chromatin with sequencing (ATAC) with select antigen profiling by sequencing (ASAPseq), provides a combination of chromatin accessibility assessments with measurements of cell-surface marker expression levels. While software exists for the characterization of these datasets, there currently exists no tool explicitly designed to reformat ASAP surface marker FASTQ data into a count matrix which can then be used for these downstream analyses. To address this, we created CountASAP, an easy-to-use Python package purposefully designed to transform FASTQ files from ASAP experiments into count matrices compatible with commonly-used downstream bioinformatic analysis packages. CountASAP takes advantage of the independence of the relevant data structures to perform fully parallelized matches of each sequenced read to user-supplied input ASAP oligos and unique cell-identifier sequences.

bioinformatics↗

bioRxiv2023

Multiplexed Methylated DNA Immunoprecipitation Sequencing (Mx-MeDIP-Seq) to Study DNA Methylation Using Low Amounts of DNA

DNA methylation is an epigenetic mark that has a crucial role in regulating gene expression. Aberrant DNA methylation results in severe diseases in humans, such as cancer, autoimmune disease, atherosclerosis, and cardiovascular diseases. Whole-genome bisulfite sequencing and methylated DNA immunoprecipitation are available to study DNA methylation changes, but they are typically used on a few samples at a time. Here, we developed a novel method called Multiplexed Methylated DNA Immunoprecipitation Sequencing (Mx-MeDIP-Seq), that can be used to analyze many DNA samples in parallel, requiring only small amounts of input DNA. In this method, 10 different DNA samples were fragmented, purified, barcoded, and pooled prior to immunoprecipitation. In a head-to-head comparison, we observed 99% correlation between MeDIP-Seq performed individually or combined as Mx-MeDIP-Seq. Moreover, multiplexed MeDIP led to more than 95% normalized percent recovery and a 25-fold enrichment ratio by qPCR, like the enrichment of the conventional method. This technique was successfully performed with as little as 25 ng of DNA, equivalent to 3400 to 6200 cells. Up to 10 different samples were processed simultaneously in a single run. Overall, the Mx-MeDIP-Seq method is cost-effective with faster processing to analyze DNA methylome, making this technique more suitable for high-throughput DNA methylome analysis.

genomics↗