Genome-wide gene expression profiling is a powerful tool for exploratory analyses, providing a high dimensional picture of the state of a biological system. However, uncontrolled variation among samples can obscure and confound the effect of variables of interest. Uncontrolled developmental variation is often a major source of unknown expression variation in developmental systems. Existing methods to sort samples from transcriptomes require many samples to infer developmental trajectories and only provide a relative pseudotime.Here we present RAPToR (Real Age Prediction from Transcriptome staging on Reference), a simple computational method to estimate the absolute developmental age of even a single sample from its gene expression with up to minutes precision. We achieve this by staging samples on high-resolution reference developmental expression profiles we build from existing time series data. We implemented RAPToR for the most common animal model systems: nematode, fruit fly, zebrafish, and mouse, and demonstrate application for non-model organisms. We show how developmental variation discovered by RAPToR can be exploited to increase power to detect differential expression and to untangle the signal of perturbations of interest even when it is completely confounded with development. We anticipate our RAPToR post-profiling staging strategy will be especially useful in large scale single organism profiling because it eliminates the need for synchronization or for a tedious and potentially difficult step of accurate staging before profiling. 1.
Genome-wide gene expression profiling is a powerful tool for exploratory analyses, providing a high dimensional picture of the state of a biological system. However, uncontrolled variation among samples can obscure and confound the effect of variables of interest. Uncontrolled developmental variation is often a major source of unknown expression variation in developmental systems. Existing methods to sort samples from transcriptomes require many samples to infer developmental trajectories and only provide a relative pseudo-time. Here we present RAPToR (Real Age Prediction from Transcriptome staging on Reference), a simple computational method to estimate the absolute developmental age of even a single sample from its gene expression with up to minutes precision. We achieve this by staging samples on high-resolution reference developmental expression profiles we build from existing time series data. We implemented RAPToR for the most common animal model systems: nematode, fruit fly, zebrafish, and mouse, and demonstrate application for non-model organisms. We show how developmental variation discovered by RAPToR can be exploited to increase power to detect differential expression and to untangle the signal of perturbations of interest even when it is completely confounded with development. We anticipate our RAPToR post-profiling staging strategy will be especially useful in large scale single organism profiling because it eliminates the need for synchronization or for a tedious and potentially difficult step of accurate staging before profiling.
Here, we describe how the speed of C/EBPα-induced B cell to macrophage transdifferentiation (BMT) can be regulated, using both mouse and human models. The identification of a mutant of C/EBPα (C/EBPαR35A) that greatly accelerates BMT helped to illuminate the mechanism. Thus, incoming C/EBPα binds to PU.1, an obligate partner expressed in B cells, leading to the release of PU.1 from B cell enhancers, chromatin closing and silencing of the B cell program. Released PU.1 redistributes to macrophage enhancers newly occupied by C/EBPα, causing chromatin opening and activation of macrophage genes. All these steps are accelerated by C/EBPαR35A, initiated by its increased affinity for PU.1. Wild-type C/EBPα is methylated by Carm1 at arginine 35 and the enzyme’s perturbations modulate BMT velocity as predicted from the observations with the mutant. Increasing the proportion of unmethylated C/EBPα in granulocyte/macrophage progenitors by inhibiting Carm1 biases the cell’s differentiation toward macrophages, suggesting that cell fate decision velocity and lineage directionality are closely linked processes.
Cell fate decisions are driven by lineage-restricted transcription factors but how they are regulated is incompletely understood. The C/EBPa-induced B cell to macrophage transdifferentiation (BMT) is a powerful system to address this question. Here we describe that C/EBPa with a single arginine mutation (C/EBPaR35A) induces a dramatically accelerated BMT in mouse and human cells. Changes in the expression of lineage-restricted genes occur as early as within 1 hour compared to 18 hours with the wild type. Mechanistically C/EBPaR35A exhibits an increased affinity for PU.1, a bi-lineage transcription factor required for C/EBPa-induced BMT. The complex induces more rapid chromatin accessibility changes and an enhanced relocation (stealing) of PU.1 from B cell to myeloid gene regulatory elements. Arginine 35 is methylated by Carm1 and inhibition of the enzyme accelerates BMT, as seen with the mutant. Our data suggest that the relative proportions of methylated and unmethylated C/EBPa in bipotent progenitors determine the velocity of cell fate choice and also affect lineage directionality. This could represent a more general mechanism that coordinates the speed and faithfulness of cell fate conversions.
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