Our lab is performing single cell RNAseq and mapping the reads back to an existing genome. We are running paired-end sequencing on a NextSeq 500 to analyze differential expression patterns between cell types. I am having difficulty deciding how narrow a range to size select for (using Pippin Prep) after adding adapter sequences. I am aware that tighter size selection reduces bias during bridge amplification, and that the bioinformatics are typically happier with narrower size ranges, but I want to make sure that my size distribution is broad enough to capture a representative sample. What size ranges are people using in their research? Do people feel that selecting transcripts in the 250-300 bp size range would be representative, or should I go tighter/broader? My Covaris sheared libraries currently span 50-1000 bp with the peaks around 300 bp. Any feedback is greatly appreciated!
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The field of epigenetics has traditionally concentrated more on DNA and how changes like methylation and phosphorylation of histones impact gene expression and regulation. However, our increased understanding of RNA modifications and their importance in cellular processes has led to a rise in epitranscriptomics research. “Epitranscriptomics brings together the concepts of epigenetics and gene expression,” explained Adrien Leger, PhD, Principal Research Scientist on Modified Bases...-
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Proteins are often described as the workhorses of the cell, and identifying their sequences is key to understanding their role in biological processes and disease. Currently, the most common technique used to determine protein sequences is mass spectrometry. While still a valuable tool, mass spectrometry faces several limitations and requires a highly experienced scientist familiar with the equipment to operate it. Additionally, other proteomic methods, like affinity assays, are constrained...-
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04-04-2024, 04:25 PM -
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