Drought constitutes a noteworthy abiotic stressor, detrimentally impacting seed germination, plant development, and agricultural yield. In response to the threats imposed by climate change and water paucity, this study examined the morphological divergence and genetic governance of drought resilience traits at the germination stage in 196 rapeseed (Brassica napus L.) lines under both normal (0 MPa) and drought-induced stress (−0.8 MPa) scenarios. Our study showed that the composite drought tolerance D value is a reliable index for identifying drought resilience. Through a genome-wide association study (GWAS), we uncovered 37 significant SNP loci and 136 putative genes linked to drought tolerance based on the D value. A key discovery included the gene BnaA01g29390D (BnNCED3), encoding 9-cis-epoxycarotenoid dioxygenase, which exhibited significantly heightened expression levels in drought-resistant accessions (p < 0.01), underscoring its potential as a positive drought stress regulator and a suitable candidate for genetically enhancing drought resilience. Moreover, we pinpointed four stress-reactive transcription factors (BnaA07g26740D, BnaA07g26870D, BnaA07g26910D, and BnaA07g26980D), two E3 ubiquitin-protein ligases (BnaA05g22900D and BnaC06g28950D), two enzymes (BnaA01g29390D and BnaA03g48550D), and two photosystem-associated proteins (BnaA05g22950D and BnaC06g28840D) as vital components in drought response mechanisms. The construction of a regulatory network reveals an ABA-dependent pathway (NCED3/RGLG5/IDD14) that contributes to drought tolerance in rapeseed seedlings, alongside the involvement of a drought avoidance strategy (APRR6/PHYB). The SNPs and genes unveiled in this study offer a substantial theoretical foundation for subsequent investigations targeting genetic improvement for drought resilience during seed germination in rapeseed.
Quantifying relevant interactions between neural populations is a prominent question in the analysis of high-dimensional neural recordings. However, existing dimension reduction methods often discuss communication in the absence of a formal framework, while frameworks proposed to address this gap are impractical in data analysis. This work bridges the formal framework of M-Information Flow with practical analysis of real neural data. To this end, we propose Iterative Regression, a message-dependent linear dimension reduction technique that iteratively finds an orthonormal basis such that each basis vector maximizes correlation between the projected data and the message. We then define 'M-forwarding' to formally capture the notion of a message being forwarded from one neural population to another. We apply our methodology to recordings we collected from two neural populations in a simplified model of whisker-based sensory detection in mice, and show that the low-dimensional M-forwarding structure we infer supports biological evidence of a similar structure between the two original, high-dimensional populations.
Mats W. J. van Es, Chetan Gohil, Andrew J. Quinn
et al.
We describe OHBA Software Library for the analysis of electrophysiological data (osl-ephys). This toolbox builds on top of the widely used MNE-Python package and provides unique analysis tools for magneto-/electro-encephalography (M/EEG) sensor and source space analysis, which can be used modularly. In particular, it facilitates processing large amounts of data using batch parallel processing, with high standards for reproducibility through a config API and log keeping, and efficient quality assurance by producing HTML processing reports. It also provides new functionality for doing coregistration, source reconstruction and parcellation in volumetric space, allowing for an alternative pipeline that avoids the need for surface-based processing, e.g., through the use of Fieldtrip. Here, we introduce osl-ephys by presenting examples applied to a publicly available M/EEG data (the multimodal faces dataset). osl-ephys is open-source software distributed on the Apache License and available as a Python package through PyPi and GitHub.
Laura Lopez-Cruz, Benjamin U. Phillips, Jonathan M. Hailwood
et al.
AbstractEffort-based decision-making is impaired in multiple psychopathologies leading to significant impacts on the daily life of patients. Preclinical studies of this important transdiagnostic symptom in rodents are hampered, however, by limitations present in currently available decision-making tests, including the presence of delayed reinforcement and off-target cognitive demands. Such possible confounding factors can complicate the interpretation of results in terms of decision-making per se. In this study we addressed this problem using a novel touchscreen Rearing-Effort Discounting (RED) task in which mice choose between two single-touch responses: rearing up to touch an increasingly higher positioned stimulus to obtain a High Reward (HR) or touching a lower stimulus to obtain a Low Reward (LR). To explore the putative advantages of this new approach, RED was compared with a touchscreen version of the well-studied Fixed Ratio-based Effort Discounting (FRED) task, in which multiple touches are required to obtain an HR, and a single response is required to obtain an LR. Results from dopaminergic (haloperidol and d-amphetamine), behavioral (changes in the order of effort demand; fixed-ratio schedule in FRED or response height in RED), and dietary manipulations (reward devaluation by pre-feeding) were consistent with the presence of variables that may complicate interpretation of conventional decision-making tasks, and demonstrate how RED appears to minimize such variables.
Noise is a ubiquitous feature of the physical world. As a result, the first prerequisite of life is fault tolerance: maintaining integrity of state despite external bombardment. Recent experimental advances have revealed that biological systems achieve fault tolerance by implementing mathematically intricate error-correcting codes and by organizing in a modular fashion that physically separates functionally distinct subsystems. These elaborate structures represent a vanishing volume in the massive genetic configuration space. How is it possible that the primitive process of evolution, by which all biological systems evolved, achieved such unusual results? In this work, through experiments in Boolean networks, we show that the simultaneous presence of error correction and modularity in biological systems is no coincidence. Rather, it is a typical co-occurrence in noisy dynamic systems undergoing evolution. From this, we deduce the principle of error correction enhanced evolvability: systems possessing error-correcting codes are more effectively improved by evolution than those without.
A general model is presented for coupling of high-Q whispering-gallery modes in optical microsphere resonators with coupler devices that possess a discrete and continuous spectrum of propagating modes. By contrast to conventional high-Q optical cavities, in microspheres the independence of high intrinsic quality-factor and controllable parameters of coupling via an evanescent field offer a variety of regimes similar to those that are already available in rf devices. The theory is applied to data reported earlier on different types of couplers to microsphere resonators and is complemented by the experimental demonstration of enhanced coupling efficiency (∼80%) and variable loading regimes with Q>108 fused-silica microspheres.