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Color pattern mimicry in Heliconius butterflies is a classic case study of complex trait adaptation via selection on a few large effect genes. Association studies have linked color pattern variation to a handful of noncoding regions, yet the presumptive cis-regulatory elements (CREs) that control color patterning remain unknown. Here we combine chromatin assays, DNA sequence associations, and genome editing to functionally characterize 5 cis-regulatory elements of the color pattern gene optix. We were surprised to find that the cis-regulatory architecture of optix is characterized by pleiotropy and regulatory fragility, where deletion of individual cis-regulatory elements has broad effects on both color pattern and wing vein development. Remarkably, we found orthologous cis-regulatory elements associate with wing pattern convergence of distantly related comimics, suggesting that parallel coevolution of ancestral elements facilitated pattern mimicry. Our results support a model of color pattern evolution in Heliconius where changes to ancient, multifunctional cis-regulatory elements underlie adaptive radiation.

Fibrolamellar carcinoma (FLC) is a rare malignancy disproportionately affecting adolescents and young adults with no curative therapy. FLC is characterized by thick stroma, which has long suggested an important role of the tumor microenvironment. Over the past decade, several studies have revealed aberrant chromatin activity and gene expression in FLC. However, an important limitation of these efforts is that they were conducted on bulk tumor samples. Consequently, the cell types that contribute to the different epigenomic and transcriptional features of FLC have remained unknown. In this study we primarily leverage single nucleus ATAC-seq, along with supporting single nucleus RNA-seq, to unveil cell-type specific signal for chromatin activity, microRNAs, transcription factor networks (such as CREB3L1), and super enhancers including those nearby to notable FLC-enriched genes such as CDH11 and SLC16A14 . The results provide a high resolution map of chromatin features of FLC, which in turn affords the opportunity to study cell type specific transcriptional reprogramming in the FLC tumor microenvironment.

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. Animal husbandry and hunting has increased human exposure to pathogens. Here, the authors investigate the evolution of human host gene expression to Bacillus anthracis infection, the bacterium that causes anthrax disease. They observe recent positive selection, suggestive of human genome adaptation to anthrax disease.

Ovulation is induced by the luteinizing hormone (LH) surge and accompanied by granulosa cell luteinization and ovarian angiogenesis. Semaphorin 3E (Sema3E)‐Plexin‐D1 pathway regulates angiogenesis in other tissues, but its role in the ovary is unknown. Evidence indicates that Sema3E‐Plexin‐D1 pathway plays an important role in the mouse ovary. The expression of Sema3E and its receptor, Plexin‐D1, is dynamically regulated in the mouse ovary downstream of the LH surge. This regulation requires the modulation of chromatin accessibility by CCAAT/enhancer‐binding proteins α and β. Intraovarian injection of recombinant Sema3E results in reduced ovulation, impaired corpus luteum formation, and aberrant ovarian angiogenesis. These in vivo physiological abnormalities are consistent with altered expression of genes regulating these processes, and with data from in vitro cultured granulosa cells and ovarian stromal tissues treated with Sema3E or neutralizing antibody of Plexin‐D1. The findings pinpoint Sema3E‐Plexin‐D1 pathway as a potential therapeutic target for fertility and infertility management. The Semaphorin 3E (Sema3E)‐Plexin‐D1 pathway mediated by C/EBPα and C/EBPβ downstream of the luteinizing hormone (LH) surge plays important roles in the mouse preovulatory ovary. Timely activation and suppression of this pathway during the preovulatory stage are crucial for ovulation, corpus luteum formation, and proper angiogenesis. The Sema3E‐Plexin‐D1 pathway may serve as a potential new therapeutic target for managing ovulation and luteal function.

Heat shock (HS) initiates rapid, extensive, and evolutionarily conserved changes in transcription that are accompanied by chromatin decondensation and nucleosome loss at HS loci. Here we have employed in situ Hi-C to determine how heat stress affects longrange chromatin conformation in human and Drosophila cells. We found that compartments and topologically associating domains (TADs) remain unchanged by an acute HS. Knockdown of Heat Shock Factor 1 (HSF1), the master transcriptional regulator of the HS response, identified HSF1-dependent genes and revealed that up-regulation is often mediated by distal HSF1 bound enhancers. HSF1-dependent genes were usually found in the same TAD as the nearest HSF1 binding site. Although most interactions between HSF1 binding sites and target promoters were established in the nonheat shock (NHS) condition, a subset increased contact frequency following HS. Integrating information about HSF1 binding strength, RNA polymerase abundance at the HSF1 bound sites (putative enhancers), and contact frequency with a target promoter accurately predicted which up-regulated genes were direct targets of HSF1 during HS. Our results suggest that the chromatin conformation necessary for a robust HS response is preestablished in NHS cells of diverse metazoan species.

Abstract Motivation Haplotagging is a method for linked-read sequencing, which leverages the cost-effectiveness and throughput of short-read sequencing while retaining part of the long-range haplotype information captured by long-read sequencing. Despite its utility and advantages over similar methods, existing linked-read analytical pipelines are incompatible with haplotagging data. Results We describe Harpy, a modular and user-friendly software pipeline for processing all stages of haplotagged linked-read data, from raw sequence data to phased genotypes and structural variant detection. Availability and implementation https://github.com/pdimens/harpy.

Functional element annotations are critical tools used to provide insight into the molecular processes governing cell development, differentiation, and disease. Run-on and sequencing assays measure the production of nascent RNAs and can provide an effective data source for discovering functional elements. However, the accurate inference of functional elements from run-on sequencing data remains an open problem because the signal is noisy and challenging to model. Here we investigated computational approaches that convert run-on and sequencing data into annotations representing transcription units, including genes and non-coding RNAs. We developed a convolutional neural network, called convolutional discovery of gene anatomy using PRO-seq (CGAP), trained to identify different anatomical features of a transcription unit, which were then stitched together into transcript annotations using a hidden Markov model (HMM). Comparison with existing methods showed a significant performance improvement using our novel CGAP-HMM approach. We developed a voting system that ensembles the top three annotation strategies, resulting in large and significant improvements in transcription unit annotation accuracy over the best performing individual method. Finally, we also report a conditional generative adversarial network (cGAN) as a generative approach to transcription unit annotation that shows promise for further development. Collectively our work provides novel tools for transcription unit annotation from run-on and sequencing data that are accurate enough to be useful in many applications.

Fibrolamellar carcinoma (FLC) is a rare malignancy disproportionately affecting adolescents and young adults with no standard of care. FLC is characterized by thick stroma, which has long suggested an important role of the tumor microenvironment. Over the past decade, several studies have revealed aberrant markers and pathways in FLC. However, a significant drawback of these efforts is that they were conducted on bulk tumor samples. Consequently, identities and roles of distinct cell types within the tumor milieu, and the patterns of intercellular communication, have yet to be explored. In this study we unveil cell-type specific gene signatures, transcription factor networks, and super-enhancers in FLC using a multi-omics strategy that leverages both single-nucleus ATAC-seq and single-nucleus RNA-seq. We also infer completely rewired cell-to-cell communication patterns in FLC including signaling mediated by SPP1-CD44, MIF-ACKR3, GDF15-TGFBR2, and FGF7-FGFR. Finally, we validate findings with loss-of-function studies in several models including patient tissue slices, identifying vulnerabilities that merit further investigation as candidate therapeutic targets in FLC.

Naive CD8+ T cells are a heterogeneous population, with different subsets possessing distinct functions and kinetics upon activation. However, the gene regulatory circuits differentiating these naive subsets are not well studied. In this work, we analyzed a large collection of public and newly generated RNA seq and ATAC seq profiles of different subsets of naive CD8+ T cells, revealing significant differences in the gene regulatory landscapes between subsets. We leveraged these data by employing a network inference algorithm, Inferelator, to identify the transcriptional regulatory circuits active in each subset. The predicted transcriptional network of the naive CD8+ T cell pool was validated by multiple orthogonal approaches, including CUT&Tag and Micro-C. Interestingly, our network analysis revealed a novel role for Eomes in promoting effector cell differentiation in specific cell subsets. Moreover, we uncovered multiple novel regulators across a variety of subsets and discovered several modules of genes that were co-regulated by shared sets of transcription factors in distinct subsets. Collectively, our data defines the gene regulatory programs differentiating naive CD8+ T cells and facilitates the identification of novel transcription factors that may alter the propensity of naive CD8+ T cells to become effector or memory cells after infection.Competing Interest StatementThe authors have declared no competing interest.

ME/CFS is a serious and poorly understood disease. To understand immune dysregulation in ME/CFS, we used single-cell RNA-seq (scRNA-seq) to examine immune cells in cohorts of patients and controls. Post-exertional malaise (PEM), an exacerbation of symptoms following strenuous exercise, is a characteristic symptom of ME/CFS. Thus, to detect changes coincident with PEM, we also performed scRNA-seq on the same cohorts following exercise. At baseline, ME/CFS patients displayed dysregulation of classical monocytes suggestive of inappropriate differentiation and migration to tissue. We were able to identify both diseased and more normal monocytes within patients, and the fraction of diseased cells correlated with metrics of disease severity. Comparing the transcriptome at baseline and post-exercise challenge, we discovered patterns indicative of improper platelet activation in patients, with minimal changes elsewhere in the immune system. Taken together, these data identify immunological defects present at baseline in patients and an additional layer of dysregulation following exercise. Competing Interest Statement The authors have declared no competing interest.