Biology subjects

Henriquez, C.

Publications and source records attributed to Henriquez, C..

3 recordsLinked to original sources

bioRxiv2020

Diversification, disparification, and hybridization in the desert shrubs Encelia

O_LIThere are multiple hypotheses for the spectacular plant diversity found in deserts. We explore how different factors, including the roles of ecological opportunity and selection, promote diversification and disparification in Encelia, a lineage of woody plants in the deserts of the Americas. C_LIO_LIUsing a nearly complete species-level phylogeny along with a broad set of phenotypic traits, we estimate divergence times and diversification rates, identify instances of hybridization, quantify trait disparity, and assess phenotypic divergence across environmental gradients. C_LIO_LIWe show that Encelia originated and diversified recently (mid-Pleistocene) and rapidly, with rates comparable to notable adaptive radiations in plants. Encelia probably originated in the hot deserts of North America, with subsequent diversification across steep environmental gradients. We uncover multiple instances of gene flow between species. The radiation of Encelia is characterized by fast rates of phenotypic evolution, trait lability, and extreme disparity across environments and between species-pairs with overlapping geographic ranges. C_LIO_LIEncelia exemplifies how interspecific gene flow in combination with high trait lability can enable exceptionally fast diversification and disparification across steep environmental gradients. C_LI

evolutionary biology↗

bioRxiv2020

Tamoxifen reduces inflammatory infiltration of neutrophils in the airways.

ABSTRACTTamoxifen is a drug of choice for treatment of breast cancer but it has also been reported to bear anti-inflammatory activity. Previously, we have observed that tamoxifen treatment successfully reduced inflammation in horses affected by equine asthma syndrome. More notorious, tamoxifen was effective at reducing the infiltration of neutrophils in the inflamed airways by a mechanism that increases efferocytosis, allowing the resolution of inflammation. Due to the emerging increase in patients with chronic inflammatory lung diseases, there is an urgent need for therapies that help reduce airway inflammation. Thus we tested the effect of tamoxifen on airway neutrophil infiltration by using three different mouse models for acute and chronic inflammation of the lung. We found that the drug was able to produce a significant reduction in neutrophils in all scenarios. Ussing chamber experiments demonstrated that tamoxifen has no effect on fluid secretion and absorption, discarding a possible reduction in mucociliary clearance due to the known ion-channel blocking effects of tamoxifen. Since this drug has been largely used in human medicine, tamoxifen might be a “low hanging fruit” for a novel anti-inflammatory therapy for airway diseases characterized by neutrophilic inflammation.Competing Interest StatementThe authors have declared no competing interest.View Full Text

pharmacology and toxicology↗

bioRxiv2018

Exploiting regulatory heterogeneity to systematically identify enhancers with high accuracy

Identifying functional enhancers elements in metazoan systems is a major challenge. For example, large-scale validation of enhancers predicted by ENCODE reveal false positive rates of at least 70%. Here we use the pregrastrula patterning network of Drosophila melanogaster to demonstrate that loss in accuracy in held out data results from heterogeneity of functional signatures in enhancer elements. We show that two classes of enhancer are active during early Drosophila embryogenesis and that by focusing on a single, relatively homogeneous class of elements, over 98% prediction accuracy can be achieved in a balanced, completely held-out test set. The class of well predicted elements is composed predominantly of enhancers driving multi-stage, segmentation patterns, which we designate segmentation driving enhancers (SDE). Prediction is driven by the DNA occupancy of early developmental transcription factors, with almost no additional power derived from histone modifications. We further show that improved accuracy is not a property of a particular prediction method: after conditioning on the SDE set, naive Bayes and logistic regression perform as well as more sophisticated tools. Applying this method to a genome-wide scan, we predict 1,640 SDEs that cover 1.6% of the genome, 916 of which are novel. An analysis of 32 novel SDEs using wholemount embryonic imaging of stably integrated reporter constructs chosen throughout our prediction rank-list showed >90% drove expression patterns. We achieved 86.7% precision on a genome-wide scan, with an estimated recall of at least 98%, indicating high accuracy and completeness in annotating this class of functional elements.\n\nSignificance StatementWe demonstrate a high accuracy method for predicting enhancers genome wide with > 85% precision as validated by transgenic reporter assays in Drosophila embryos. This is the first time such accuracy has been achieved in a metazoan system, allowing us to predict with high-confidence 1640 enhancers, 916 of which are novel. The predicted enhancers are demarcated by heterogeneous collections of epigenetic marks; many strong enhancers are free from classical indicators of activity, including H3K27ac, but are bound by key transcription factors. H3K27ac, often used as a one-dimensional predictor of enhancer activity, is an uninformative parameter in our data.

genomics↗