Bayesian localization of CNV candidates in WGS data within minutes

Background: Full Bayesian inference for detecting copy number variants (CNV) from whole-genome sequencing (WGS) data is still largely infeasible due to computational demands. A recently introduced approach to perform Forward-Backward Gibbs sampling using dynamic Haar wavelet compression has alleviated issues of convergence and, to some extent, speed. Yet, the problem remains challenging in practice. Results: In this paper, we propose an improved algorithmic framework for this approach. We provide new space-efficient data structures to query sufficient statistics in logarithmic time, based on a linear-Time, in-place transform of the data, which also improves on the compression ratio. We also propose a new approach to efficiently store and update marginal state counts obtained from the Gibbs sampler. Conclusions: Using this approach, we discover several CNV candidates in two rat populations divergently selected for tame and aggressive behavior, consistent with earlier results concerning the domestication syndrome as well as experimental observations. Computationally, we observe a 29.5-fold decrease in memory, an average 5.8-fold speedup, as well as a 191-fold decrease in minor page faults. We also observe that metrics varied greatly in the old implementation, but not the new one. We conjecture that this is due to the better compression scheme. The fully Bayesian segmentation of the entire WGS data set required 3.5 min and 1.24 GB of memory, and can hence be performed on a commodity laptop

Restart Solar: How NYC Can Renew Its Solar Program To Benefit Workers & Community

New York City intends to install 100 MW of solar on the rooftops of public buildings by 2025. Over the next nine years, this upgrading of public infrastructure could provide significant benefits for New Yorkers, and not just in terms of reducing emissions. These solar installations, impacting over 300 public buildings, can create thousands of good, union jobs for New York residents, and significantly reduce the City's electricity bill, freeing up funds for new and innovative programs that generate wealth in our communities. Despite the clear opportunities for leveraging this solar program to the benefit of communities and workers, this report finds that New York City's public rooftop solar energy initiative can do more to address the needs of our City's low-income communities and workers

Integrated computational and Drosophila cancer model platform captures previously unappreciated chemicals perturbing a kinase network

Drosophila provides an inexpensive and quantitative platform for measuring whole animal drug response. A complementary approach is virtual screening, where chemical libraries can be efficiently screened against protein target(s). Here, we present a unique discovery platform integrating structure-based modeling with Drosophila biology and organic synthesis. We demonstrate this platform by developing chemicals targeting a Drosophila model of Medullary Thyroid Cancer (MTC) characterized by a transformation network activated by oncogenic dRetM955T. Structural models for kinases relevant to MTC were generated for virtual screening to identify unique preliminary hits that suppressed dRetM955T-induced transformation. We then combined features from our hits with those of known inhibitors to create a ‘hybrid’ molecule with improved suppression of dRetM955T transformation. Our platform provides a framework to efficiently explore novel kinase inhibitors outside of explored inhibitor chemical space that are effective in inhibiting cancer networks while minimizing whole body toxicity

Somatic mutant clones colonize the human esophagus with age.

The extent to which cells in normal tissues accumulate mutations throughout life is poorly understood. Some mutant cells expand into clones that can be detected by genome sequencing. We mapped mutant clones in normal esophageal epithelium from nine donors (age range, 20 to 75 years). Somatic mutations accumulated with age and were caused mainly by intrinsic mutational processes. We found strong positive selection of clones carrying mutations in 14 cancer genes, with tens to hundreds of clones per square centimeter. In middle-aged and elderly donors, clones with cancer-associated mutations covered much of the epithelium, with NOTCH1 and TP53 mutations affecting 12 to 80% and 2 to 37% of cells, respectively. Unexpectedly, the prevalence of NOTCH1 mutations in normal esophagus was several times higher than in esophageal cancers. These findings have implications for our understanding of cancer and aging.Wellcome Trust Cancer Research U

Long-term expansion, genomic stability and in vivo safety of adult human pancreas organoids

Abstract: Background: Pancreatic organoid systems have recently been described for the in vitro culture of pancreatic ductal cells from mouse and human. Mouse pancreatic organoids exhibit unlimited expansion potential, while previously reported human pancreas organoid (hPO) cultures do not expand efficiently long-term in a chemically defined, serum-free medium. We sought to generate a 3D culture system for long-term expansion of human pancreas ductal cells as hPOs to serve as the basis for studies of human pancreas ductal epithelium, exocrine pancreatic diseases and the development of a genomically stable replacement cell therapy for diabetes mellitus. Results: Our chemically defined, serum-free, human pancreas organoid culture medium supports the generation and expansion of hPOs with high efficiency from both fresh and cryopreserved primary tissue. hPOs can be expanded from a single cell, enabling their genetic manipulation and generation of clonal cultures. hPOs expanded for months in vitro maintain their ductal morphology, biomarker expression and chromosomal integrity. Xenografts of hPOs survive long-term in vivo when transplanted into the pancreas of immunodeficient mice. Notably, mouse orthotopic transplants show no signs of tumorigenicity. Crucially, our medium also supports the establishment and expansion of hPOs in a chemically defined, modifiable and scalable, biomimetic hydrogel. Conclusions: hPOs can be expanded long-term, from both fresh and cryopreserved human pancreas tissue in a chemically defined, serum-free medium with no detectable tumorigenicity. hPOs can be clonally expanded, genetically manipulated and are amenable to culture in a chemically defined hydrogel. hPOs therefore represent an abundant source of pancreas ductal cells that retain the characteristics of the tissue-of-origin, which opens up avenues for modelling diseases of the ductal epithelium and increasing understanding of human pancreas exocrine biology as well as for potentially producing insulin-secreting cells for the treatment of diabetes

Somatic mutation landscapes at single-molecule resolution.

Somatic mutations drive the development of cancer and may contribute to ageing and other diseases1,2. Despite their importance, the difficulty of detecting mutations that are only present in single cells or small clones has limited our knowledge of somatic mutagenesis to a minority of tissues. Here, to overcome these limitations, we developed nanorate sequencing (NanoSeq), a duplex sequencing protocol with error rates of less than five errors per billion base pairs in single DNA molecules from cell populations. This rate is two orders of magnitude lower than typical somatic mutation loads, enabling the study of somatic mutations in any tissue independently of clonality. We used this single-molecule sensitivity to study somatic mutations in non-dividing cells across several tissues, comparing stem cells to differentiated cells and studying mutagenesis in the absence of cell division. Differentiated cells in blood and colon displayed remarkably similar mutation loads and signatures to their corresponding stem cells, despite mature blood cells having undergone considerably more divisions. We then characterized the mutational landscape of post-mitotic neurons and polyclonal smooth muscle, confirming that neurons accumulate somatic mutations at a constant rate throughout life without cell division, with similar rates to mitotically active tissues. Together, our results suggest that mutational processes that are independent of cell division are important contributors to somatic mutagenesis. We anticipate that the ability to reliably detect mutations in single DNA molecules could transform our understanding of somatic mutagenesis and enable non-invasive studies on large-scale cohorts

Single-cell transcriptomes from human kidneys reveal the cellular identity of renal tumors.

Messenger RNA encodes cellular function and phenotype. In the context of human cancer, it defines the identities of malignant cells and the diversity of tumor tissue. We studied 72,501 single-cell transcriptomes of human renal tumors and normal tissue from fetal, pediatric, and adult kidneys. We matched childhood Wilms tumor with specific fetal cell types, thus providing evidence for the hypothesis that Wilms tumor cells are aberrant fetal cells. In adult renal cell carcinoma, we identified a canonical cancer transcriptome that matched a little-known subtype of proximal convoluted tubular cell. Analyses of the tumor composition defined cancer-associated normal cells and delineated a complex vascular endothelial growth factor (VEGF) signaling circuit. Our findings reveal the precise cellular identities and compositions of human kidney tumors

Crowdsourced identification of multi-target kinase inhibitors for RET- and TAU- based disease: the Multi-Targeting Drug DREAM Challenge

A continuing challenge in modern medicine is the identification of safer and more efficacious drugs. Precision therapeutics, which have one molecular target, have been long promised to be safer and more effective than traditional therapies. This approach has proven to be challenging for multiple reasons including lack of efficacy, rapidly acquired drug resistance, and narrow patient eligibility criteria. An alternative approach is the development of drugs that address the overall disease network by targeting multiple biological targets (‘polypharmacology’). Rational development of these molecules will require improved methods for predicting single chemical structures that target multiple drug targets. To address this need, we developed the Multi-Targeting Drug DREAM Challenge, in which we challenged participants to predict single chemical entities that target pro-targets but avoid anti-targets for two unrelated diseases: RET-based tumors and a common form of inherited Tauopathy. Here, we report the results of this DREAM Challenge and the development of two neural network-based machine learning approaches that were applied to the challenge of rational polypharmacology. Together, these platforms provide a potentially useful first step towards developing lead therapeutic compounds that address disease complexity through rational polypharmacology

Additional file 3: Table S2. of Identification of genomic variants putatively targeted by selection during dog domestication

Results of Tukey’s range test for ANOVA of Mean Fst in 50kb windows around functional categories of sites with Fst > = 0.75. (DOCX 99 kb

Additional file 6: Figure S2. of Identification of genomic variants putatively targeted by selection during dog domestication

Histogram of mean Fst scores calculated in 500kb windows genome-wide between dogs and wolves. Histogram of mean Fst calculated in 500kb genomic windows across the autosome and X chromosome between dogs and wolves. Counts are included above each bin. The long tail towards positive mean Fst scores is potentially indicative of positive selection. (DOCX 71 kb