How DNA sequence affects the dynamics and position of RNA Polymerase II (Pol II) during transcription remains poorly understood. Here, we used naturally occurring genetic variation in F1 hybrid mice to explore how DNA sequence differences affect the genome-wide distribution of Pol II. We measured the position and orientation of Pol II in eight organs collected from heterozygous F1 hybrid mice using ChRO-seq. Our data revealed a strong genetic basis for the precise coordinates of transcription initiation and promoter proximal pause, allowing us to redefine molecular models of core transcriptional processes. Our results implicate DNA sequence, including both known and novel DNA sequence motifs, as key determinants of the position of Pol II initiation and pause. We report evidence that initiation site selection follows a stochastic process similar to Brownian motion along the DNA template. We found widespread differences in the position of transcription termination, which impact the primary structure and stability of mature mRNA. Finally, we report evidence that allelic changes in transcription often affect mRNA and ncRNA expression across broad genomic domains. Collectively, we reveal how DNA sequences shape core transcriptional processes at single nucleotide resolution in mammals.

The advent of animal husbandry and hunting increased human exposure to zoonotic pathogens. To understand how a zoonotic disease may have influenced human evolution, we study changes in human expression of anthrax toxin receptor 2 (ANTXR2), which encodes a cell surface protein necessary for Bacillus anthracis virulence toxins to cause anthrax disease. In immune cells, ANTXR2 is 8-fold down-regulated in all available human samples compared to non-human primates, indicating regulatory changes early in the evolution of modern humans. We also observe multiple genetic signatures consistent with recent positive selection driving a European-specific decrease in ANTXR2 expression in multiple tissues affected by anthrax toxins. Our observations fit a model in which humans adapted to anthrax disease following early ecological changes associated with hunting and scavenging, as well as a second period of adaptation after the rise of modern agriculture.

Background: X and Y chromosome analysis is a critical component of genetic testing, used both diagnostically and as a quality control (QC) metric. Discordances between expected and observed sex chromosome data can arise due to mislabeling, demographic data errors, transplant history, or biological variations. Such discordances pose challenges to laboratories and affect patient care, particularly in marginalized populations and unique clinical contexts. Methods: We reviewed cases of sex chromosome discordance identified at our laboratory from January 2021 through August 2023. Cases spanned various testing methods and were categorized by the root cause, including mislabeling, sample mix-ups, transgender individuals, stem cell transplants, and unexplained causes. Case outcomes were assessed, and potential resolutions were analyzed. Results: Among 65 cases identified, the leading cause of discordance was mislabeling (n = 20, 31%), followed by other/not identified (n = 16, 25%), sample mix-ups (n = 13, 20%), transgender individuals (n = 9, 14%), and stem cell transplants (n = 7, 11%). Cases required additional QC processes such as reanalysis, clinician contact, and occasionally sample re-collection. The process extended turnaround times by up to 13 business days. Detailed case reviews highlighted the challenges and implications of managing these discordances, emphasizing the importance of accurate data transmission and inclusive practices. Conclusion: Using X and Y chromosome data as a QC metric can identify critical errors but also introduces limitations and bias. Improved standardization, inclusive practices, and alternative QC methods are necessary to ensure accuracy and equitable patient care. Collaborative efforts are required to address demographic complexities and reduce testing delays.

The role of histone modifications in transcription remains incompletely understood. Here we used experimental perturbations combined with sensitive machine learning tools that infer the distribution of histone marks using maps of nascent transcription. Transcription predicted the variation in active histone marks and complex chromatin states, like bivalent promoters, down to single-nucleosome resolution and at an accuracy that rivaled the correspondence between independent ChIP-seq experiments. Blocking transcription rapidly removed two punctate marks, H3K4me3 and H3K27ac, from chromatin indicating that transcription is required for active histone modifications. Transcription was also required for maintenance of H3K27me3 consistent with a role for RNA in recruiting PRC2. A subset of DNase-I hypersensitive sites were refractory to prediction, precluding models where transcription initiates pervasively at any open chromatin. Our results, in combination with past literature, support a model in which active histone modifications serve a supportive, rather than a regulatory, role in transcription.