Whole-Genome Resequencing of Wild and Cultivated Cannabis Reveals the Genetic Structure and Adaptive Selection of Important Traits

Background: Cannabis is an important industrial crop, whose bast fiber, seed, flowers and leaves are widely used by humans，especially cannabinoids extracted from plants as medicine is a hot spot in recent years. China is one of the origins of cannabis, where it has been cultivated and utilized for more than 6000 years, with the largest planting area of industrial hemp at present. China is rich in cannabis germplasm resources covering different latitudes (23 to 51°N) and is one of the few countries with wild cannabis resources. However, the genetic structure of Chinese cannabis populations and the adaptive selection of important traits remain unclear.Results: We identified the main morphological and physiological characteristics of wild cannabis and defined the genetic structure and relationships among wild and cultivated Chinese cannabis accessions and foreign representatives. This suggested that wild resources in Xinjiang have played an important role in the process of cannabis domestication. Adaptive selection analysis revealed that cultivated cannabis has undergone selective evolution or adaptation in flowering, growth and stress tolerance, and many functional genes were identified. Flowering characteristics analysis implied that wild cannabis is native to high latitudes and possesses the typical characteristic of early flowering, while cultivated cannabis has undergone a process of adaptive evolution to adjust to natural photoperiod conditions in different latitudes through regulation of FT-like expression.Conclusion: This study clarifies the genetic structure of Chinese cannabis and provides insight into adaptive selection and breeding in cannabis.

Machine learning enables discovery of DNA-carbon nanotube sensors for serotonin

DNA-wrapped single walled carbon nanotube (SWNT) conjugates have remarkable optical properties leading to their use in biosensing and imaging applications. A critical limitation in the development of DNA-SWNT sensors is the current inability to predict unique DNA sequences that confer a strong analyte-specific optical response to these sensors. Here, near-infrared (nIR) fluorescence response datasets for ~100 DNA-SWNT conjugates, narrowed down by a selective evolution protocol starting from a pool of ~1010 unique DNA-SWNT candidates, are used to train machine learning (ML) models to predict new unique DNA sequences with strong optical response to neurotransmitter serotonin. First, classifier models based on convolutional neural networks (CNN) are trained on sequence features to classify DNA ligands as either high response or low response to serotonin. Second, support vector machine (SVM) regression models are trained to predict relative optical response values for DNA sequences. Finally, we demonstrate with validation experiments that integrating the predictions of ensembles of the highest quality CNN classifiers and SVM regression models leads to the best predictions of both high and low response sequences. With our ML approaches, we discovered five new DNA-SWNT sensors with higher fluorescence intensity response to serotonin than obtained previously. Overall, the explored ML approaches introduce an important new tool to predict useful DNA sequences, which can be used for discovery of new DNA-based sensors and nanobiotechnologies.

Assessment of the evolutionary consequence of putative driver mutations in colorectal cancer with spatial multiomic data

Cancer genomic medicine relies on targeting driver genes. However, current catalogues of cancer drivers are mostly based on indirect measurements of mutation frequencies, positions or types, rather than their effect on clonal expansions in vivo. Moreover, nongenetic drivers are largely unknown, as are the epigenetic and transcriptomic effects of genetic drivers. Here we perform spatial computational inference on multiomic data with matched whole-genome sequencing, ATAC-seq and RNA-seq. Using 436 samples, we directly quantify the contribution, or lack thereof, of putative driver genes to subclonal expansions in vivo in 30 colorectal carcinomas (4-33 samples per patient, median=15). Although subclonal neutral evolution was widespread (13/26 cases with sufficient data), there were cases with clear evidence of subclonal selection (6/26) in which we measured epigenetic and transcriptomic differences between subclones in vivo. In 7/26 cases we could not distinguish between neutral or selective evolution with the available data. We identified expanding subclones that were not driven by known genetic alterations, and propose candidate epigenetic drivers. We identified the distinguishing patterns of genomic heterogeneity produced in fast, exponentially growing tumours (7/26) versus neoplasms growing only at the periphery (19/26), as well as identifying clonally intermixed (16/28 cases with sufficient data) versus segregated malignancies (10/28). Our model-based approach measures genetic and non-genetic subclonal selection, or lack thereof, in space and time and allows in vivo comparisons of the emergent phenotypic properties of subclones within human tumours.

The essence of the intelligent and innovation potential of a mining engineer

The problem of slow innovative development in the mining industry in Russia has urged the studies into the structure and meaning of the intelligent and innovative potential of mining engineers. The review of literature and terminology on the notion of intelligence together with understanding and generalization of the collected knowledge revealed the functions and contents of the intellectual and innovative activities of a human being. The studies into the essence of the human intellect components made it possible to develop a functional hierarchy model of brainwork. The role and behavior of each component of intellect in the process of generation and implementation of engineering innovations are examined. The structure, forms and results of activity done by the cognitive components of intellect are determined. The definition of the conception of «innovation» is presented. Numerous definitions of the notion of «innovation» are reviewed, and their specifics and versions for mines are determined. The notion of «innovation» is defined for the mining industry as a result of introduction or improvement of tangible or intangible assets for implementation and producing beneficial effects in a mine. The essence of the scientific concept of «potential» is described as a set of methods, capabilities, reserves, sources and resources activatable and applicable in problem solving. Three levels and forms of appearance of a potential representative of its dynamics in time are described. The onthological background of advance as a transition from potential to real is shown. The essence of the intelligent and innovative potential of a mining engineer is defined as a degree of revealing intelligent and creative abilities of the mental power for organizational and technological innovations in combination with energy and will towards their efficient practical application in subsoil management. The in-depth insight into the concept content opens the door toward its next-level studying, modeling, assessment and selective evolution.

Anti-’68ers and the Racist-Libertarian Alliance

This article shows that the incorporation of right-wing libertarians into the Alt Right coalition was the end result of a schism in the neoliberal intellectual movement in response to the egalitarian challenge of the 1960s. In a symmetry with developments on the post-Marxist Left, one group of Austrian School economists associated with F. A. Hayek took a cultural turn. Performing their own critique of “economism,” they perceived human nature as rooted primarily in culture, adaptable over time through social learning and selective evolution. The other group of Austrian economists, linked to Murray Rothbard and culminating in the racist-libertarian alliance of the Alt Right, saw difference as rooted in biology and race as an immutable hierarchy of group traits and abilities. While many observers have described the Alt Right as a backlash against the excesses of neoliberalism, this shows that an important current of the Alt Right was born within and not against the neoliberal movement.

Photonic Inverse Design of Simple Particles with Realistic Losses in the Visible Frequency Range

Billions of U.S. dollars of basic and applied research funding have been invested during the last few years in ideas proposing inverse concepts. The photonics market could not make an exception to this global trend, and thus, several agenda-setting research groups have already started providing sophisticated tools, constrained optimization algorithms, and selective evolution techniques towards this direction. Here, we present an approach of inverse design based on the exhaustive trial-and-testing of the available media and changing the physical dimensions’ range according to the operational wavelength. The proposed technique is applied to the case of an optimal radiation-enhancing cylindrical particle fed by a line source of visible light and gives a two-order increase in the magnitude of the produced signal.

The Puzzle of HIV Neutral and Selective Evolution

HIV is one of the fastest evolving organisms known. It evolves about 1 million times faster than its host, humans. Because HIV establishes chronic infections, with continuous evolution, its divergence within a single infected human surpasses the divergence of the entire humanoid history. Yet, it is still the same virus, infecting the same cell types and using the same replication machinery year after year. Hence, one would think that most mutations that HIV accumulates are neutral. But the picture is more complicated than that. HIV evolution is also a clear example of strong positive selection, that is, mutants have a survival advantage. How do these facts come together?