Project Summary Mobile element insertions (MEIs), or transposable elements, have been established to contribute to ongoing mutagenesis of the human genome, leading to widespread variability and sporadic cases of human disease. Recent work has begun to illuminate underlying roles through which MEIs affect regulatory processes through their combined effects on transcription factor binding and 3D chromatin looping. Recent work from our group has demonstrated the importance of MEIs in establishing chromatin looping variability in driving differential gene expression. These observations have precipitated development of molecular and computational approaches to study their impact on human biology, including whole-genome and target-capture strategies leveraging short- read sequencing technologies. However, these methods fail to accurately capture the entire landscape of MEIs within the human genome because of their limited ability to identify non-reference polymorphic MEIs. This failure derives in part from a blind-spot of short-read genome sequencing: because the human genome harbors over 1 million MEIs, unambiguous alignment of short reads is problematic. Given the demonstrated importance of MEIs to human biology and evolution, it is imperative that novel methods capable of comprehensively mapping their locations across many human genomes be developed. In this proposal we aim to 1) Quantify the effects of TE activity on CTCF binding in a human population sample of 51 well-studied individuals using computational meth- ods, 2) Map invariant and polymorphic LTR13 insertions in the CEU population and investigate their effects on intraspecies variability in CTCF binding, chromatin looping, and gene regulation, and 3) Directly map HARVK/LTR13-anchored chromatin loops through enrichment-capture combined with ONT-based chromatin conformation capture sequencing. We expect completion of these aims to yield the following outcomes: We will: 1) Present the first reliable estimate of the contribution of polymorphic MEIs to CTCF-mediated chromatin looping variation in a human population. 2) Improve understanding of how fixed and polymorphic MEIs contribute to population-level variability in regulatory activity, gene expression, and disease risk. 3) Demonstrate causality of ongoing MEI activity regarding population-level looping variation and differential gene expression. The new meth- ods proposed here will address the shortcomings of existing short-read sequencing technologies, allowing us to comprehensively and cost-effectively map target MEIs across a broad population sample, bridging important gaps in our knowledge of how gene regulatory processes evolve in the human genome.