Here we describe Protein Interaction Quantitation (PIQ), a computational method that models the magnitude and shape of genome-wide DNase profiles to facilitate the identification of transcription factor (TF) binding sites. Through the use of machine learning techniques, PIQ identified binding sites for >700 TFs from one DNase-seq experiment with accuracy comparable to ChIP-seq for motif-associated TFs (median AUC=0.93 across 303 TFs). We applied PIQ to analyze DNase-seq data from mouse embryonic stem cells differentiating into pre-pancreatic and intestinal endoderm. We identified (n=120) and experimentally validated eight ‘pioneer’ TF families that dynamically open chromatin, enabling other TFs to bind to adjacent DNA. Four pioneer TF families only open chromatin in one direction from their motifs. Furthermore, we identified a class of ‘settler’ TFs whose genomic binding is principally governed by proximity to open chromatin. Our results support a model of hierarchical TF binding in which directional and non-directional pioneer activity shapes the chromatin landscape for population by settler TFs.
Significance
Human pluripotent stem cells (hPSCs) can be produced from any person and have the potential to differentiate into any cell type in the body. This study focuses on the generation of insulin-expressing cells from hPSCs and compares their gene expression, as assayed by transcriptional gene products, to that of insulin-expressing β cells from human fetal and adult samples. We employ a new method to isolate and profile insulin-expressing cells and conclude that several different hPSC lines generate very similar insulin-expressing cells, cells whose transcripts resemble fetal rather than adult β cells. This study advances the possibility of directing the differentiation of stem cells into functional β cells by comparing and cataloging differences between hPSC-derived insulin-expressing cells and human β cells.
During face mask ventilation in the delivery room, V(T) and face mask leak were large and variable. The resuscitators were unable to accurately assess their face mask leak or delivered V(T).
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