Durham, T. | bioRxiv Science

bioRxiv2018

Towards inferring causal gene regulatory networks from single cell expression measurements

Single-cell transcriptome sequencing now routinely samples thousands of cells, potentially providing enough data to reconstruct causal gene regulatory networks from observational data. Here, we present Scribe, a toolkit for detecting and visualizing causal regulatory interactions between genes and explore the potential for single-cell experiments to power network reconstruction. Scribe employs Restricted Directed Information to determine causality by estimating the strength of information transferred from a potential regulator to its downstream target. We apply Scribe and other leading approaches for causal network reconstruction to several types of single-cell measurements and show that there is a dramatic drop in performance for \"pseudotime\" ordered single-cell data compared to true time series data. We demonstrate that performing causal inference requires temporal coupling between measurements. We show that methods such as \"RNA velocity\" restore some degree of coupling through an analysis of chromaffin cell fate commitment. These analyses therefore highlight an important shortcoming in experimental and computational methods for analyzing gene regulation at single-cell resolution and point the way towards overcoming it.

genomics↗

bioRxiv2018

Functional Characterization of Enhancer Evolution in the Primate Lineage

BackgroundEnhancers play an important role in morphological evolution and speciation by controlling the spatiotemporal expression of genes. Due to technological limitations, previous efforts to understand the evolution of enhancers in primates have typically studied many enhancers at low resolution, or single enhancers at high resolution. Although comparative genomic studies reveal large-scale turnover of enhancers, a specific understanding of the molecular steps by which mammalian or primate enhancers evolve remains elusive.\n\nResultsWe identified candidate hominoid-specific liver enhancers from H3K27ac ChIP-seq data. After locating orthologs in 11 primates spanning [~]40 million years, we synthesized all orthologs as well as computational reconstructions of 9 ancestral sequences for 348 \"active tiles\" of 233 putative enhancers. We concurrently tested all sequences (20 per tile) for regulatory activity with STARR-seq in HepG2 cells, with the goal of characterizing the evolutionary-functional trajectories of each enhancer. We observe groups of enhancer tiles with coherent trajectories, most of which can be explained by one or two mutational events per tile. We quantify the correlation between the number of mutations along a branch and the magnitude of change in functional activity. Finally, we identify 57 mutations that correlate with functional changes; these are enriched for cytosine deamination events within CpGs, compared to background events.\n\nConclusionsWe characterized the evolutionary-functional trajectories of hundreds of liver enhancers throughout the primate phylogeny. We observe subsets of regulatory sequences that appear to have gained or lost activity at various positions in the primate phylogeny. We use these data to quantify the relationship between sequence and functional divergence, and to identify CpG deamination as a potentially important force in driving changes in enhancer activity during primate evolution.

genomics↗