Interplay of cis and trans mechanisms driving transcription factor binding and gene expression evolution

Abstract

Noncoding regulatory variants play a central role in the genetics of human diseases and in evolution. Here we measure allele-specific transcription factor binding occupancy of three liver-specific transcription factors between crosses of two inbred mouse strains to elucidate the regulatory mechanisms underlying transcription factor binding variations in mammals. Our results highlight the pre-eminence of cis-acting variants on transcription factor occupancy divergence. Transcription factor binding differences linked to cis-acting variants generally exhibit additive inheritance, while those linked to trans-acting variants are most often dominantly inherited. Cis-acting variants lead to local coordination of transcription factor occupancies that decay with distance; distal coordination is also observed and may be modulated by long-range chromatin contacts. Our results reveal the regulatory mechanisms that interplay to drive transcription factor occupancy, chromatin state, and gene expression in complex mammalian cell states.

Cis acting variation is common, can propagates across multiple regulatory layers, but is often buffered in developmental programs

“…As the two homologous chromosomes in F1 cells have a common nuclear trans environment, allelic ratios in F1s estimate cis-based differences between the two parents. Differences in parental read counts not reflected in F1 allelic-ratios give an estimate of trans-acting contributions to between line divergence (Landry et al 2005;Tirosh et al 2009;Goncalves et al 2012;Wong et al 2017).…”

“…Allelic-specific data provides a unique opportunity to study the molecular mechanisms of cisacting variation and has uncovered multiple regulatory processes through which cis-acting variation impacts transcriptional control (Kilpinen et al 2013;Chen et al 2016). F1 crosses of inbred strains provide an elegant method to determine the contribution of both cis and trans variation by overcoming the limits of genetic variation between trios and the general lack of statistical power to interrogate trans-acting variation using population data (Wittkopp et al 2004;Tirosh et al 2009;Goncalves et al 2012;Wong et al 2017). Taking advantage of this F1 design, we set out to better understand how natural sequence variation impacts gene regulation during embryonic development.…”

Causal Gene Regulatory Network Modeling and Genomics: Second-Generation Challenges

“…The initiation of RNA synthesis that this triggers might be expected to reflect an initiation frequency distribution with a continuous-valued relationship between effective transcription factor binding and RNA output in a given cell. Measurements at the population level appear to agree with this expectation in most cases: Lower positive regulator inputs or mutationally weakened cis-regulatory DNA sequences often yield lower gene expression, as averaged over the population (Goncalves et al, 2012;Ulirsch et al, 2014;Wong et al, 2017). However, an important insight into gene regulation at the single-cell level is that transcription states of a gene are often stochastically distributed in a population of nominally equivalent cells (Raj and van Oudenaarden, 2008).…”

Variation in PU.1 binding and chromatin looping at neutrophil enhancers influences autoimmune disease susceptibility

“…Transcription factor occupancy has been shown to act predominantly through cis regulatory SNPs, where coordination of cis-acting variants has been shown to decay with increasing physical distance of SNPs from bound regions 30 . To assess the potential sharing of our tfQTLs across cell types, we additionally generated PU.1 binding maps in primary monocytes (CD14 + CD16 − ) isolated from ten BLUEPRINT donors 7 , five of which overlap with the neutrophil PU.1 dataset.…”