Phyolin: Identifying a Linear Perfect Phylogeny in Single-Cell DNA Sequencing Data of Tumors

Cancer arises from an evolutionary process where somatic mutations occur and eventually give rise to clonal expansions. Modeling this evolutionary process as a phylogeny is useful for treatment decision-making as well as understanding evolutionary patterns across patients and cancer types. However, cancer phylogeny inference from single-cell DNA sequencing data of tumors is challenging due to limitations with sequencing technology and the complexity of the resulting problem. Therefore, as a first step some value might be obtained from correctly classifying the evolutionary process as either linear or branched. The biological implications of these two high-level patterns are different and understanding what cancer types and which patients have each of these trajectories could provide useful insight for both clinicians and researchers. Here, we introduce the Linear Perfect Phylogeny Flipping Problem as a means of testing a null model that the tree topology is linear and show that it is NP-hard. We develop Phyolin and, through both in silico experiments and real data application, show that it is an accurate, easy to use and a reasonably fast method for classifying an evolutionary trajectory as linear or branched

Hierarchically Porous Gd3+-Doped CeO2 Nanostructures for the Remarkable Enhancement of Optical and Magnetic Properties

Rare earth ion-doped CeO2 has attracted more and more attention because of its special electrical, optical, magnetic, or catalytic properties. In this paper, a facile electrochemical deposition route was reported for the direct growth of the porous Gd-doped CeO2. The formation process of Gd-doped CeO2 composites was investigated. The obtained deposits were characterized by SEM, EDS, XRD, and XPS. The porous Gd3+- doped CeO2 (10 at% Gd) displays a typical type I adsorption isotherm and yields a large specific surface area of 135 m2/g. As Gd3+ ions were doped into CeO2 lattice, the absorption spectrum of Gd3+-doped CeO2 nanocrystals exhibited a red shift compared with porous CeO2 nanocrystals and bulk CeO2, and the luminescence of Gd3+-doped CeO2 deposits was remarkably enhanced due to the presence of more oxygen vacancies. In addition, the strong magnetic properties of Gd-doped CeO2 (10 at% Gd) were observed, which may be caused by Gd3+ ions or more oxygen defects in deposits. In addition, the catalytic activity of porous Gd-doped CeO2 toward CO oxidation was studied

Gene Flow in Genetically Modified Wheat

Understanding gene flow in genetically modified (GM) crops is critical to answering questions regarding risk-assessment and the coexistence of GM and non-GM crops. In two field experiments, we tested whether rates of cross-pollination differed between GM and non-GM lines of the predominantly self-pollinating wheat Triticum aestivum. In the first experiment, outcrossing was studied within the field by planting “phytometers” of one line into stands of another line. In the second experiment, outcrossing was studied over distances of 0.5–2.5 m from a central patch of pollen donors to adjacent patches of pollen recipients. Cross-pollination and outcrossing was detected when offspring of a pollen recipient without a particular transgene contained this transgene in heterozygous condition. The GM lines had been produced from the varieties Bobwhite or Frisal and contained Pm3b or chitinase/glucanase transgenes, respectively, in homozygous condition. These transgenes increase plant resistance against pathogenic fungi. Although the overall outcrossing rate in the first experiment was only 3.4%, Bobwhite GM lines containing the Pm3b transgene were six times more likely than non-GM control lines to produce outcrossed offspring. There was additional variation in outcrossing rate among the four GM-lines, presumably due to the different transgene insertion events. Among the pollen donors, the Frisal GM line expressing a chitinase transgene caused more outcrossing than the GM line expressing both a chitinase and a glucanase transgene. In the second experiment, outcrossing after cross-pollination declined from 0.7–0.03% over the test distances of 0.5–2.5 m. Our results suggest that pollen-mediated gene flow between GM and non-GM wheat might only be a concern if it occurs within fields, e.g. due to seed contamination. Methodologically our study demonstrates that outcrossing rates between transgenic and other lines within crops can be assessed using a phytometer approach and that gene-flow distances can be efficiently estimated with population-level PCR analyses

Populist Mobilization: A New Theoretical Approach to Populism*

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/112280/1/j.1467-9558.2011.01388.x.pd

Metabolic Profiling of a Mapping Population Exposes New Insights in the Regulation of Seed Metabolism and Seed, Fruit, and Plant Relations

To investigate the regulation of seed metabolism and to estimate the degree of metabolic natural variability, metabolite profiling and network analysis were applied to a collection of 76 different homozygous tomato introgression lines (ILs) grown in the field in two consecutive harvest seasons. Factorial ANOVA confirmed the presence of 30 metabolite quantitative trait loci (mQTL). Amino acid contents displayed a high degree of variability across the population, with similar patterns across the two seasons, while sugars exhibited significant seasonal fluctuations. Upon integration of data for tomato pericarp metabolite profiling, factorial ANOVA identified the main factor for metabolic polymorphism to be the genotypic background rather than the environment or the tissue. Analysis of the coefficient of variance indicated greater phenotypic plasticity in the ILs than in the M82 tomato cultivar. Broad-sense estimate of heritability suggested that the mode of inheritance of metabolite traits in the seed differed from that in the fruit. Correlation-based metabolic network analysis comparing metabolite data for the seed with that for the pericarp showed that the seed network displayed tighter interdependence of metabolic processes than the fruit. Amino acids in the seed metabolic network were shown to play a central hub-like role in the topology of the network, maintaining high interactions with other metabolite categories, i.e., sugars and organic acids. Network analysis identified six exceptionally highly co-regulated amino acids, Gly, Ser, Thr, Ile, Val, and Pro. The strong interdependence of this group was confirmed by the mQTL mapping. Taken together these results (i) reflect the extensive redundancy of the regulation underlying seed metabolism, (ii) demonstrate the tight co-ordination of seed metabolism with respect to fruit metabolism, and (iii) emphasize the centrality of the amino acid module in the seed metabolic network. Finally, the study highlights the added value of integrating metabolic network analysis with mQTL mapping

How is tailored implementation undertaken using a self-guided toolkit? Qualitative study of the ItFits-toolkit in the ImpleMentAll project

BackgroundThe process of tailored implementation is ill-defined and under-explored. The ItFits-toolkit was developed and subsequently tested as a self-guided online platform to facilitate implementation of tailored strategies for internet-based cognitive behavioural therapy (iCBT) services. In ImpleMentAll, ItFits-toolkit had a small but positive effect on the primary outcome of iCBT normalisation. This paper investigates, from a qualitative perspective, how implementation teams developed and undertook tailored implementation using the toolkit within the trial.MethodsImplementation teams in thirteen sites from nine countries (Europe and Australia) used the ItFits-toolkit for six months minimum, consistent with the trial protocol. A qualitative process evaluation was conducted. Descriptive data regarding goals, barriers, strategies, and implementation plans collected within the toolkit informed qualitative data collection in real time. Qualitative data included remote longitudinal interviews (n = 55) with implementation team members (n = 30) and observations of support calls (n = 19) with study sites. Qualitative data were analysed thematically, using a team-based approach.ResultsImplementation teams developed and executed tailored implementation projects across all steps in the toolkit process. Working in a structured way but with room for flexibility, decisions were shaped by team members' ideas and goals, iterative stakeholder engagement, internal and external influences, and the context of the ImpleMentAll project. Although teams reported some positive impacts of their projects, 'time', both for undertaking the work, and for seeing project impacts, was described as a key factor in decisions about implementation strategies and assessments of success.ConclusionThis study responds directly to McHugh et al.'s (2022) call for empirical description of what implementation tailoring looks like in action, in service settings. Self-guided facilitation of tailored implementation enables implementers in service settings to undertake tailoring within their organisations. Implementation tailoring takes considerable time and involves detailed work but can be supported through the provision of implementation science informed guidance and materials, iterative and ongoing stakeholder engagement, and working reflectively in response to external influencing factors. Directions for advancement of tailored implementation are suggested

Assessment of variation in immunosuppressive pathway genes reveals TGFBR2 to be associated with risk of clear cell ovarian cancer.

BACKGROUND: Regulatory T (Treg) cells, a subset of CD4+ T lymphocytes, are mediators of immunosuppression in cancer, and, thus, variants in genes encoding Treg cell immune molecules could be associated with ovarian cancer. METHODS: In a population of 15,596 epithelial ovarian cancer (EOC) cases and 23,236 controls, we measured genetic associations of 1,351 SNPs in Treg cell pathway genes with odds of ovarian cancer and tested pathway and gene-level associations, overall and by histotype, for the 25 genes, using the admixture likelihood (AML) method. The most significant single SNP associations were tested for correlation with expression levels in 44 ovarian cancer patients. RESULTS: The most significant global associations for all genes in the pathway were seen in endometrioid ( p = 0.082) and clear cell ( p = 0.083), with the most significant gene level association seen with TGFBR2 ( p = 0.001) and clear cell EOC. Gene associations with histotypes at p < 0.05 included: IL12 ( p = 0.005 and p = 0.008, serous and high-grade serous, respectively), IL8RA ( p = 0.035, endometrioid and mucinous), LGALS1 ( p = 0.03, mucinous), STAT5B ( p = 0.022, clear cell), TGFBR1 ( p = 0.021 endometrioid) and TGFBR2 ( p = 0.017 and p = 0.025, endometrioid and mucinous, respectively). CONCLUSIONS: Common inherited gene variation in Treg cell pathways shows some evidence of germline genetic contribution to odds of EOC that varies by histologic subtype and may be associated with mRNA expression of immune-complex receptor in EOC patients

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead