Evolutionarily informed deep learning methods for predicting relative transcript abundance from DNA sequence

Deep learning methodologies have revolutionized prediction in many fields and show potential to do the same in molecular biology and genetics. However, applying these methods in their current forms ignores evolutionary dependencies within biological systems and can result in false positives and spurious conclusions. We developed two approaches that account for evolutionary relatedness in machine learning models: (i) gene-family–guided splitting and (ii) ortholog contrasts. The first approach accounts for evolution by constraining model training and testing sets to include different gene families. The second approach uses evolutionarily informed comparisons between orthologous genes to both control for and leverage evolutionary divergence during the training process. The two approaches were explored and validated within the context of mRNA expression level prediction and have the area under the ROC curve (auROC) values ranging from 0.75 to 0.94. Model weight inspections showed biologically interpretable patterns, resulting in the hypothesis that the 3′ UTR is more important for fine-tuning mRNA abundance levels while the 5′ UTR is more important for large-scale changes

Author Correction: Genome-Guided Phylo-Transcriptomic Methods and the Nuclear Phylogenetic Tree of the Paniceae Grasses

The original version of this Article contained an error in the title of the paper, where the word “Phylogenetic” was incorrectly given as “Phylogentic”. This has now been corrected in the PDF and HTML versions of the Article, and in the accompanying Supplementary Information file

Aryl hydrocarbon receptor-mediated activity of particulate organic matter from the Paso del Norte airshed along the U.S.-Mexico border.

In this study, we determined the biologic activity of dichloromethane-extracted particulate matter < 10 micro m in aerodynamic diameter (PM10) obtained from filters at three sites in the Paso del Norte airshed, which includes El Paso, Texas, USA; Juarez, Chihuahua, Mexico, and Sunland Park, New Mexico, USA. The extracts were rich in polycyclic aromatic hydrocarbons (PAHs) and had significant biologic activity, measured using two in vitro assay systems: ethoxyresorufin-(O-deethylase (EROD) induction and the aryl hydrocarbon-receptor luciferase reporter system. In most cases, both EROD (5.25 pmol/min/mg protein) and luciferase activities (994 relative light units/mg) were highest in extracts from the Advance site located in an industrial neighborhood in Juarez. These values represented 58% and 55%, respectively, of induction associated with 1 micro M ss-naphthoflavone exposures. In contrast, little activity was observed at the Northeast Clinic site in El Paso, the reference site. In most cases, luciferase and EROD activity from extracts collected from the Tillman Health Center site, situated in downtown El Paso, fell between those observed at the other two sites. Overall, a statistically significant correlation existed between PM10 and EROD and luciferase activities. Chemical analysis of extracts collected from the Advance site demonstrated that concentrations of most PAHs were higher than those reported in most other metropolitan areas in the United States. Calculations made with these data suggest a cancer risk of 5-12 cases per 100,000 people. This risk estimate, as well as comparisons with the work of other investigators, raises concern regarding the potential for adverse health effects to the residents of this airshed. Further work is needed to understand the sources, exposure, and effects of PM10 and particulate organic material in the Paso del Norte airshed

Distinct C4 sub-types and C3 bundle sheath isolation in the Paniceae grasses.

Funder: U.S. Department of Agriculture; Id: http://dx.doi.org/10.13039/100000199Funder: University of Missouri; Id: http://dx.doi.org/10.13039/100007165In C4 plants, the enzymatic machinery underpinning photosynthesis can vary, with, for example, three distinct C4 acid decarboxylases being used to release CO2 in the vicinity of RuBisCO. For decades, these decarboxylases have been used to classify C4 species into three biochemical sub-types. However, more recently, the notion that C4 species mix and match C4 acid decarboxylases has increased in popularity, and as a consequence, the validity of specific biochemical sub-types has been questioned. Using five species from the grass tribe Paniceae, we show that, although in some species transcripts and enzymes involved in multiple C4 acid decarboxylases accumulate, in others, transcript abundance and enzyme activity is almost entirely from one decarboxylase. In addition, the development of a bundle sheath isolation procedure for a close C3 species in the Paniceae enables the preliminary exploration of C4 sub-type evolution

Shot noise in mesoscopic systems

This is a review of shot noise, the time-dependent fluctuations in the electrical current due to the discreteness of the electron charge, in small conductors. The shot-noise power can be smaller than that of a Poisson process as a result of correlations in the electron transmission imposed by the Pauli principle. This suppression takes on simple universal values in a symmetric double-barrier junction (suppression factor 1/2), a disordered metal (factor 1/3), and a chaotic cavity (factor 1/4). Loss of phase coherence has no effect on this shot-noise suppression, while thermalization of the electrons due to electron-electron scattering increases the shot noise slightly. Sub-Poissonian shot noise has been observed experimentally. So far unobserved phenomena involve the interplay of shot noise with the Aharonov-Bohm effect, Andreev reflection, and the fractional quantum Hall effect.Comment: 37 pages, Latex, 10 figures (eps). To be published in "Mesoscopic Electron Transport," edited by L. P. Kouwenhoven, G. Schoen, and L. L. Sohn, NATO ASI Series E (Kluwer Academic Publishing, Dordrecht

The Stakes in Bayh-Dole: Public Values Beyond the Pace of Innovation

Evaluation studies of the Bayh-Dole Act are generally concerned with the pace of innovation or the transgressions to the independence of research. While these concerns are important, I propose here to expand the range of public values considered in assessing Bayh-Dole and formulating future reforms. To this end, I first examine the changes in the terms of the Bayh-Dole debate and the drift in its design. Neoliberal ideas have had a definitive influence on U.S. innovation policy for the last thirty years, including legislation to strengthen patent protection. Moreover, the neoliberal policy agenda is articulated and justified in the interest of “competitiveness.” Rhetorically, this agenda equates competitiveness with economic growth and this with the public interest. Against that backdrop, I use Public Value Failure criteria to show that values such as political equality, transparency, and fairness in the distribution of the benefits of innovation, are worth considering to counter the “policy drift” of Bayh-Dole