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Phylogenetic Modeling of Regulatory Element Turnover Based on Epigenomic Data
No full textEvolutionary changes in gene expression are often driven by gains and losses of cis-regulatory elements (CREs). The dynamics of CRE evolution can be examined using multi-species epigenomic data, but so far such analyses have generally been descriptive and model-free. Here, we introduce a probabilistic modeling framework for the evolution of CREs that operates directly on raw chromatin immunoprecipitation and sequencing (ChIP-seq) data and fully considers the phylogenetic relationships among species. Our framework includes a phylogenetic hidden Markov model, called epiPhyloHMM, for identifying the locations of multiply aligned CREs, and a combined phylogenetic and generalized linear model, called phyloGLM, for accounting for the influence of a rich set of genomic features in describing their evolutionary dynamics. We apply these methods to previously published ChIP-seq data for the H3K4me3 and H3K27ac histone modifications in liver tissue from nine mammals. We find that enhancers are gained and lost during mammalian evolution at about twice the rate of promoters, and that turnover rates are negatively correlated with DNA sequence conservation, expression level, and tissue breadth, and positively correlated with distance from the transcription start site, consistent with previous findings. In addition, we find that the predicted dosage sensitivity of target genes positively correlates with DNA sequence constraint in CREs but not with turnover rates, perhaps owing to differences in the effect sizes of the relevant mutations. Altogether, our probabilistic modeling framework enables a variety of powerful new analyses
Miswired Enhancer Logic Drives a Cancer of the Muscle Lineage.
Get PDFCore regulatory transcription factors (CR TFs) establish enhancers with logical ordering during embryogenesis and development. Here we report that in fusion-positive rhabdomyosarcoma, a cancer of the muscle lineage, the chief oncogene PAX3-FOXO1 is driven by a translocated FOXO1 super enhancer (SE) restricted to a late stage of myogenesis. Using chromatin conformation capture techniques, we demonstrate that the extensive FOXO1 cis-regulatory domain interacts with PAX3. Furthermore, RNA sequencing and chromatin immunoprecipitation sequencing data in tumors bearing rare PAX translocations implicate enhancer miswiring across all fusion-positive tumors. HiChIP of H3K27ac showed connectivity between the FOXO1 SE, additional intra-domain enhancers, and the PAX3 promoter. We show that PAX3-FOXO1 transcription is diminished when this network of enhancers is ablated by CRISPR. Our data reveal a hijacked enhancer network that disrupts the stepwise CR TF logic of normal skeletal muscle development (PAX3 to MYOD to MYOG), replacing it with an "infinite loop" enhancer logic that locks rhabdomyosarcoma in an undifferentiated stage
A Pliable ERα Cistrome Evades Therapy
No full textThe transcription factor oestrogen receptor alpha (ERα) has long been targeted for therapeutic benefit in cancer, but drug resistance can emerge through a multitude of mechanisms. A study now reveals how the ERα cistrome can become reprogrammed to confer resistance to tamoxifen in breast cancer
Glyphosate Resistance Decoded: The Reference Sequence of the Extrachromosomal DNA Replicon in Amaranth
No full textIn Brief
Signatures of Sex: Sex Differences in Gene Expression in the Vertebrate Brain
No full textWomen and men differ in disease prevalence, symptoms, and progression rates for many psychiatric and neurological disorders. As more preclinical studies include both sexes in experimental design, an increasing number of sex differences in physiology and behavior have been reported. In the brain, sex-typical behaviors are thought to result from sex-specific patterns of neural activity in response to the same sensory stimulus or context. These differential firing patterns likely arise as a consequence of underlying anatomic or molecular sex differences. Accordingly, gene expression in the brains of females and males has been extensively investigated, with the goal of identifying biological pathways that specify or modulate sex differences in brain function. However, there is surprisingly little consensus on sex-biased genes across studies and only a handful of robust candidates have been pursued in the follow-up experiments. Furthermore, it is not known how or when sex-biased gene expression originates, as few studies have been performed in the developing brain. Here we integrate molecular genetic and neural circuit perspectives to provide a conceptual framework of how sex differences in gene expression can arise in the brain. We detail mechanisms of gene regulation by steroid hormones, highlight landmark studies in rodents and humans, identify emerging themes, and offer recommendations for future research
Pupil-linked Phasic Arousal Predicts a Reduction of Choice Bias Across Species and Decision Domains
Get PDFDecisions are often made by accumulating ambiguous evidence over time. The brain's arousal systems are activated during such decisions. In previous work in humans, we found that evoked responses of arousal systems during decisions are reported by rapid dilations of the pupil and track a suppression of biases in the accumulation of decision-relevant evidence (de Gee et al., 2017). Here, we show that this arousal-related suppression in decision bias acts on both conservative and liberal biases, and generalizes from humans to mice, and from perceptual to memory-based decisions. In challenging sound-detection tasks, the impact of spontaneous or experimentally induced choice biases was reduced under high phasic arousal. Similar bias suppression occurred when evidence was drawn from memory. All of these behavioral effects were explained by reduced evidence accumulation biases. Our results point to a general principle of interplay between phasic arousal and decision-making
Discovering and Validating Cancer Genetic Dependencies: Approaches and Pitfalls
No full textCancer 'genetic dependencies' - genes whose products are essential for cancer cell fitness - are promising targets for therapeutic development. However, recent evidence has cast doubt on the validity of several putative dependencies that are currently being targeted in cancer clinical trials, underscoring the challenges inherent in correctly identifying cancer-essential genes. Here we review several common techniques and platforms for discovering and characterizing cancer dependencies. We discuss the strengths and drawbacks of different gene-perturbation approaches, and we highlight the use of poorly validated genetic and pharmacological agents as a common cause of target misidentification. A careful consideration of the limitations of current technologies and cancer models will improve our ability to correctly uncover cancer genetic dependencies and will facilitate the development of improved therapeutic agents
An Epigenetic Priming Mechanism Mediated by Nutrient Sensing Regulates Transcriptional Output
No full textWhile precise tuning of gene expression levels is critical for most developmental pathways, the mechanisms by which the transcriptional output of dosage-sensitive molecules is established or modulated by the environment remain poorly understood. Here, we provide a mechanistic framework for how the conserved transcription factor BLMP-1/Blimp1 operates as a pioneer factor to decompact chromatin near its target loci hours before transcriptional activation and by doing so, regulates both the duration and amplitude of subsequent target gene transcription. This priming mechanism is genetically separable from the mechanisms that establish the timing of transcriptional induction and functions to canalize aspects of cell-fate specification, animal size regulation, and molting. A key feature of the BLMP-1-dependent transcriptional priming mechanism is that chromatin decompaction is initially established during embryogenesis and maintained throughout larval development by nutrient sensing. This anticipatory mechanism integrates transcriptional output with environmental conditions and is essential for resuming normal temporal patterning after animals exit nutrient-mediated developmental arrests
Minimum Epistasis Interpolation for Sequence-Function Relationships
Get PDFMassively parallel phenotyping assays have provided unprecedented insight into how multiple mutations combine to determine biological function. While such assays can measure phenotypes for thousands to millions of genotypes in a single experiment, in practice these measurements are not exhaustive, so that there is a need for techniques to impute values for genotypes whose phenotypes have not been directly assayed. Here, we present an imputation method based on inferring the least epistatic possible sequence-function relationship compatible with the data. In particular, we infer the reconstruction where mutational effects change as little as possible across adjacent genetic backgrounds. The resulting models can capture complex higher-order genetic interactions near the data, but approach additivity where data is sparse or absent. We apply the method to high-throughput transcription factor binding assays and use it to explore a fitness landscape for protein G