High-resolution mapping of cancer cell networks using co-functional interactions.

Powerful new technologies for perturbing genetic elements have recently expanded the study of genetic interactions in model systems ranging from yeast to human cell lines. However, technical artifacts can confound signal across genetic screens and limit the immense potential of parallel screening approaches. To address this problem, we devised a novel PCA-based method for correcting genome-wide screening data, bolstering the sensitivity and specificity of detection for genetic interactions. Applying this strategy to a set of 436 whole genome CRISPR screens, we report more than 1.5 million pairs of correlated "co-functional" genes that provide finer-scale information about cell compartments, biological pathways, and protein complexes than traditional gene sets. Lastly, we employed a gene community detection approach to implicate core genes for cancer growth and compress signal from functionally related genes in the same community into a single score. This work establishes new algorithms for probing cancer cell networks and motivates the acquisition of further CRISPR screen data across diverse genotypes and cell types to further resolve complex cellular processes

Quasars: What turns them off?

(Abridged) We explore the idea that the anti-hierarchical turn-off observed in the quasar population arises from self-regulating feedback, via an outflow mechanism. Using a detailed hydrodynamic simulation we calculate the luminosity function of quasars down to a redshift of z=1 in a large, cosmologically representative volume. Outflows are included explicitly by tracking halo mergers and driving shocks into the surrounding intergalactic medium. Our results are in excellent agreement with measurements of the spatial distribution of quasars, and we detect an intriguing excess of galaxy-quasar pairs at very short separations. We also reproduce the anti-hierarchical turnoff in the quasar luminosity function, however, the magnitude of the turn-off falls short of that observed as well as that predicted by analogous semi-analytic models. The difference can be traced to the treatment of gas heating within galaxies. The simulated galaxy cluster L_X-T relationship is close to that observed for z~1 clusters, but the simulated galaxy groups at z=1 are significantly perturbed by quasar outflows, suggesting that measurements of X-ray emission in high-redshift groups could well be a "smoking gun" for the AGN heating hypothesis.Comment: 16 pages, 11 figures, submitted to ApJ, comments welcome

Reduced signal for polygenic adaptation of height in UK Biobank

Several recent papers have reported strong signals of selection on European polygenic height scores. These analyses used height effect estimates from the GIANT consortium and replication studies. Here, we describe a new analysis based on the the UK Biobank (UKB), a large, independent dataset. We find that the signals of selection using UKB effect estimates are strongly attenuated or absent. We also provide evidence that previous analyses were confounded by population stratification. Therefore, the conclusion of strong polygenic adaptation now lacks support. Moreover, these discrepancies highlight (1) that methods for correcting for population stratification in GWAS may not always be sufficient for polygenic trait analyses, and (2) that claims of differences in polygenic scores between populations should be treated with caution until these issues are better understood.Editorial noteThis article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter)

Understanding how institutions may support the development of transdisciplinary approaches to sustainability research

This article analyses the approaches of academics seeking to engage with private, public and community-based stakeholders through transdisciplinary research about pressing sustainability challenges and, in particular, climate change; it outlines aspects of the institutional factors which influence transdisciplinary research. A qualitative approach was employed in conducting 10 semi-structured interviews to analyse the challenges and motivations of academic researchers when working with a range of other stakeholders through transdisciplinary practice. Two key contributions are made through this work. First, this article adds to the existing literature on motivations and challenges for undertaking research with private, public and community stakeholders in a cross-disciplinary manner. Second, the current institutional circumstances influencing such research practices are outlined, alongside potential ways forward. The research presented here has been undertaken in light of the experiences of the two lead co-authors as early career researchers coming from the disciplines of sociology and energy engineering, engaging in transdisciplinary research within a local community context in relation to a regional energy transition project

The SXS Collaboration catalog of binary black hole simulations

Accurate models of gravitational waves from merging black holes are necessary for detectors to observe as many events as possible while extracting the maximum science. Near the time of merger, the gravitational waves from merging black holes can be computed only using numerical relativity. In this paper, we present a major update of the Simulating eXtreme Spacetimes (SXS) Collaboration catalog of numerical simulations for merging black holes. The catalog contains 2018 distinct configurations (a factor of 11 increase compared to the 2013 SXS catalog), including 1426 spin-precessing configurations, with mass ratios between 1 and 10, and spin magnitudes up to 0.998. The median length of a waveform in the catalog is 39 cycles of the dominant $\ell=m=2$ gravitational-wave mode, with the shortest waveform containing 7.0 cycles and the longest 351.3 cycles. We discuss improvements such as correcting for moving centers of mass and extended coverage of the parameter space. We also present a thorough analysis of numerical errors, finding typical truncation errors corresponding to a waveform mismatch of $\sim 10^{-4}$. The simulations provide remnant masses and spins with uncertainties of 0.03% and 0.1% ($90^{\text{th}}$ percentile), about an order of magnitude better than analytical models for remnant properties. The full catalog is publicly available at https://www.black-holes.org/waveforms .Comment: 33+18 pages, 13 figures, 4 tables, 2,018 binaries. Catalog metadata in ancillary JSON file. v2: Matches version accepted by CQG. Catalog available at https://www.black-holes.org/waveform

PIK3CA-associated developmental disorders exhibit distinct classes of mutations with variable expression and tissue distribution

Mosaicism is increasingly recognized as a cause of developmental disorders with the advent of next-generation sequencing (NGS). Mosaic mutations of PIK3CA have been associated with the widest spectrum of phenotypes associated with overgrowth and vascular malformations. We performed targeted NGS using 2 independent deep-coverage methods that utilize molecular inversion probes and amplicon sequencing in a cohort of 241 samples from 181 individuals with brain and/or body overgrowth. We identified PIK3CA mutations in 60 individuals. Several other individuals (n = 12) were identified separately to have mutations in PIK3CA by clinical targetedpanel testing (n = 6), whole-exome sequencing (n = 5), or Sanger sequencing (n = 1). Based on the clinical and molecular features, this cohort segregated into three distinct groups: (a) severe focal overgrowth due to low-level but highly activating (hotspot) mutations, (b) predominantly brain overgrowth and less severe somatic overgrowth due to less-activating mutations, and (c) intermediate phenotypes (capillary malformations with overgrowth) with intermediately activating mutations. Sixteen of 29 PIK3CA mutations were novel. We also identified constitutional PIK3CA mutations in 10 patients. Our molecular data, combined with review of the literature, show that PIK3CA-related overgrowth disorders comprise a discontinuous spectrum of disorders that correlate with the severity and distribution of mutations

Testing gravitational-wave searches with numerical relativity waveforms: Results from the first Numerical INJection Analysis (NINJA) project

The Numerical INJection Analysis (NINJA) project is a collaborative effort between members of the numerical relativity and gravitational-wave data analysis communities. The purpose of NINJA is to study the sensitivity of existing gravitational-wave search algorithms using numerically generated waveforms and to foster closer collaboration between the numerical relativity and data analysis communities. We describe the results of the first NINJA analysis which focused on gravitational waveforms from binary black hole coalescence. Ten numerical relativity groups contributed numerical data which were used to generate a set of gravitational-wave signals. These signals were injected into a simulated data set, designed to mimic the response of the Initial LIGO and Virgo gravitational-wave detectors. Nine groups analysed this data using search and parameter-estimation pipelines. Matched filter algorithms, un-modelled-burst searches and Bayesian parameter-estimation and model-selection algorithms were applied to the data. We report the efficiency of these search methods in detecting the numerical waveforms and measuring their parameters. We describe preliminary comparisons between the different search methods and suggest improvements for future NINJA analyses.Comment: 56 pages, 25 figures; various clarifications; accepted to CQ

DNA Specificity Determinants Associate with Distinct Transcription Factor Functions

To elucidate how genomic sequences build transcriptional control networks, we need to understand the connection between DNA sequence and transcription factor binding and function. Binding predictions based solely on consensus predictions are limited, because a single factor can use degenerate sequence motifs and because related transcription factors often prefer identical sequences. The ETS family transcription factor, ETS1, exemplifies these challenges. Unexpected, redundant occupancy of ETS1 and other ETS proteins is observed at promoters of housekeeping genes in T cells due to common sequence preferences and the presence of strong consensus motifs. However, ETS1 exhibits a specific function in T cell activation; thus, unique transcriptional targets are predicted. To uncover the sequence motifs that mediate specific functions of ETS1, a genome-wide approach, chromatin immunoprecipitation coupled with high-throughput sequencing (ChIP-seq), identified both promoter and enhancer binding events in Jurkat T cells. A comparison with DNase I sensitivity both validated the dataset and also improved accuracy. Redundant occupancy of ETS1 with the ETS protein GABPA occurred primarily in promoters of housekeeping genes, whereas ETS1 specific occupancy occurred in the enhancers of T cell–specific genes. Two routes to ETS1 specificity were identified: an intrinsic preference of ETS1 for a variant of the ETS family consensus sequence and the presence of a composite sequence that can support cooperative binding with a RUNX transcription factor. Genome-wide occupancy of RUNX factors corroborated the importance of this partnership. Furthermore, genome-wide occupancy of co-activator CBP indicated tight co-localization with ETS1 at specific enhancers, but not redundant promoters. The distinct sequences associated with redundant versus specific ETS1 occupancy were predictive of promoter or enhancer location and the ontology of nearby genes. These findings demonstrate that diversity of DNA binding motifs may enable variable transcription factor function at different genomic sites

Innovative methods of community engagement: towards a low carbon climate resilient future

The proceedings of the Innovative Methods of Community Engagement: Toward a Low Carbon, Climate Resilient Future workshop have been developed by the Imagining2050 team in UCC and the Secretariat to the National Dialogue on Climate Action (NDCA). The NDCA also funded the workshop running costs. The proceedings offer a set of recommendations and insights into leveraging different community engagement approaches and methodologies in the area of climate action. They draw from interdisciplinary knowledge and experiences of researchers for identifying, mobilizing and mediating communities. The work presented below derives from a workshop held in the Environmental Research Institute in UCC on the 17th January 2019. These proceedings are complementary to an earlier workshop also funded by the NDCA and run by MaREI in UCC, titled ‘How do we Engage Communities in Climate Action? – Practical Learnings from the Coal Face’. The earlier workshop looked more closely at community development groups and other non-statutory organizations doing work in the area of climate change