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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Critical Barriers to Successful Implementation of Earth-Abundant, Mn-Rich Cathodes for Vehicle Applications and Beyond: The Effect of Particle Morphology

As the search for improved and next-generation cathodes continues, it is clear that a deeper understanding of synthesis–structure–electrochemical property relationships is of critical importance. The effects of primary and secondary particle morphologies on various transition metal oxides have been studied, but new findings are still being reported. To date, few studies have focused on the effects of particle morphologies on Li- and Mn-rich oxides (>50% Mn) and even fewer studies have focused on the influence over key properties such as electrode-level impedance. In this study, we report the effects of particle morphologies on the area-specific-impedance (ASI) and thermal behavior of Li- and Mn-rich oxides. Samples with a fixed, layered–layered–spinel (LLS), composition were synthesized with differing primary morphologies and tested under standardized, full-cell protocols. The results suggest that smaller primary particle size (i.e., higher surface area) leads to lower overall ASI, a delay in the increasing impedance at low states-of-charge (SOCs), and surprisingly, improved thermal behavior.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Dynamic Structure Discovery Applied to the Ion Transport in the Ubiquitous Lithium-ion Battery Electrolyte LP30

The electrolytes of the today omnipresent lithium-ion batteries (LIBs) have for more than 25 years been based upon 1 M LiPF 6 in a 50:50 EC:DMC mixture—commonly known as LP30. The success of the basic design of the LP30 electrolyte, with many variations and additions made over the years, is unchallenged. Yet, some molecular level fundamentals of LP30 are surprisingly elusive: the structure of the first solvation shell of the Li + cation is still a topic of current debate; the details of the dynamics are not fully understood; the interpretation of structural and dynamic properties is highly dependent on the analysis methods used; the contributions by different species to the ion transport and the energetics involved are not established. We here apply dynamic structure discovery analysis as implemented in CHAMPION to molecular dynamics simulation trajectories to bring new light on the structure and dynamics within LP30 and especially the (Li + ) ion transport to rationalize further development of LIB electrolytes.

25 ENERGY STORAGE↗
DOE OSTI2022

Investigating the Particle Growth in Bimodal Pt/C Catalysts by In-Situ Small-Angle X-ray Scattering: Challenges in the Evaluation of Stress Test Protocol-Dependent Degradation Mechanisms

The influence of different combinations of accelerated stress test (AST) protocols simulating load-cycle and start/stop conditions of a proton exchange membrane fuel cell (PEMFC) vehicle is investigated on a bimodal Pt/C catalyst. The bimodal Pt/C catalyst, prepared by mixing two commercial catalysts, serves as a model system and consists of two distinguishable size populations. The change in mean particle size was investigated by in situ small-angle X-ray scattering (SAXS). The comparison to the reference catalysts, i.e., the two single-size population catalysts, uncovers the presence of electrochemical Ostwald ripening as a degradation mechanism in the bimodal catalyst. Increasing the harshness of the applied AST protocol combinations by faster changing between load-cycle or start/stop conditions, the particle size of the larger population of the bimodal catalyst increases faster than expected. Surprisingly, the change in mean particle size of the smaller size population indicates a smaller increase for harsher AST protocols, which might be explained by a substantial electrochemical Ostwald ripening.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Low-Temperature Characterization of a Nonaqueous Liquid Electrolyte for Lithium Batteries

Rechargeable batteries exhibit poor performance at low temperatures due to sluggish ion transport through the electrolytic phase. Ion transport is governed by three transport parameters—conductivity, diffusion coefficient, and the cation transference number with respect to the solvent velocity—and the thermodynamic factor. Understanding how these parameters change with temperature is necessary for designing improved electrolytes. In this work, we combine electrochemical techniques with electrophoretic NMR to determine the temperature dependence of these parameters for a liquid electrolyte, LiTFSI salt dissolved in tetraglyme between −20 and 45 °C. At colder temperatures, all species in the electrolyte tend to move more slowly due to increasing viscosity, which translates to a monotonic decrease in conductivity and diffusion coefficient with decreasing temperature. Surprisingly, we find that the field-induced velocity of solvent molecules at a particular salt concentration is a nonmonotonic function of temperature. The cation transference number with respect to the solvent velocity thus exhibits a complex dependence on temperature and salt concentration. The measured thermodynamic and transport properties are used to predict concentration gradients that will form in a lithium-lithium symmetric cell under a constant applied potential as a function of temperature using concentrated solution theory. The calculated steady current at −20 °C is lower than that at 45 °C by roughly two orders of magnitude.

25 ENERGY STORAGE↗
DOE OSTI2022

Mappymatch FKA: YAMM (Yet Another Map-Matcher) [SWR 22-38]

A surprisingly non-trivial technical challenge is to associate points in space (e.g., GPS data) with specific segments of a road network or map. The software package ( allows users to match GPS point data to a road network (commonly known as "map matching"). The software is designed such that a user could match a set of GPS points to a variety of different road network representations using a variety of map matching algorithms. There are currently several "built-in" road networks and map matching algorithms but the software has been designed to enable new ones to be added with minimal overhead.

Reinicke, Nicholas↗
DOE OSTI2022

FutureTense

Protective vaccines and reliable diagnostics are essential tools for controlling viral diseases. However, the efficacy of these tools can be diminished by mutations in viral genomes. The delay between the emergence of new viral strains and the redesign of vaccines and diagnostics allows for continued viral transmission. Is it possible to address this challenge by computationally predicting viral genome sequence evolution? Can we “future-proof” vaccines and diagnostics by targeting both current and anticipated future sequence variants? While predicting viral evolution is still an unsolved, “grand challenge” problem in biology, the large, and rapidly growing, number of SARS-CoV-2 genome sequences provide an opportunity to quantify the ability of machine learning to predict viral genome sequence evolution. Towards this end, we have developed a simple computational model for predicting viral evolution at the level of individual nucleotides. The key metric for quantifying the per-base, prediction accuracy for viral evolution is the Mann-Whitney U statistic (or, equivalently, the area under the receiver operator curve). Since the Mann-Whitney U statistic is not a differentiable function, existing deep leaning packages (like Pytorch and Keras/TensorFlow) are not useful, as they require that the accuracy metric/objective function be analytically differentiable with respect to the model parameters. To overcome this challenge, we have implemented custom software, “FutureTense”, that can train a machine learning model by maximizing the non-differentiable Mann-Whitney U statistic. This software trains a machine learning model by exploring along the direction of the discrete gradient of the Mann-Whitney U statistic in the model parameter space. Parallel computing and genome sequence-specific optimizations are used to accelerate model training. The resulting machine learning model learns the observed high C->U mutation rates in the SARS-CoV-2 genome (which are potentially induced by host defenses) and provides prediction accuracies that are significantly better than one would expect from random chance. While predicting viral evolution is still quite far from a solved problem, the surprising performance of this simple model gives hope that the accuracy of predicting viral genome evolution can be further increased by more sophisticated approaches.

Gans, Jason↗
DOE OSTI2021

Learning Universal Authorship Representations

This code contains all the utilities required to reproduce the results of our EMNLP 2021 paper "Learning Universal Authorship Representations". It contains the utilities required for download the datasets, training our model, and performing all evaluations necessary for reproducing the results in the paper. Here's the abstract of our work: Determining whether two documents were composed by the same author, also known as authorship verification, has traditionally been tackled using statistical methods. Recently, authorship representations learned using neural networks have been found to outperform alternatives, particularly in large-scale settings involving hundreds of thousands of authors. But do such representations learned in a particular domain transfer to other domains? Or are these representations inherently entangled with domain-specific features? To study these questions, we conduct the first large-scale study of cross-domain transfer for authorship verification considering zero-shot transfers involving three disparate domains: Amazon reviews, fanfiction short stories, and Reddit comments. We find that although a surprising degree of transfer is possible between certain do- mains, it is not so successful between others. We examine properties of these domains that influence generalization and propose simple but effective methods to improve transfer.

Rivera Soto, RafaelA↗
DOE OSTI2025

On the Effectiveness of Neural Operators at Zero-Shot Weather Downscaling [SWR-25-20]

Code repository for the experiments performed in the paper: On the Effectiveness of Neural Operators at Zero-Shot Weather Downscaling (https://doi.org/10.1017/eds.2025.11) Overall, our work investigates the zero-shot downscaling potential of neural operators. To summarize, our contributions are: 1. We provide a comparative analysis based on two challenging weather downscaling problems, between various neural operator and non-neural-operator methods with large upsampling factors (e.g., 8x and 15x) and fine grid resolutions (e.g., 2 km × 2 km wind speed). 2. We examine whether neural operator layers provide unique advantages when testing downscaling models on upsampling factors higher than those seen during training, i.e., zero-shot downscaling. Our results instead show the surprising success of an approach that combines a powerful transformer-based model with a parameter-free interpolation step at zero-shot weather downscaling. 3. We find that this Swin-Transformer-based approach mostly outperforms all neural operator models in terms of average error metrics, whereas an enhanced super-resolution generative adversarial network (ESRGAN)-based approach is better than most models in capturing the physics of the system, and suggests their use in future work as strong baselines. However, these approaches still do not capture variations at smaller spatial scales well, including the physical characteristics of turbulence in the HR data. This suggests a potential for improvement in transformer or GAN-based methods and neural-operator-based methods for zero-shot weather downscaling.

Sinha, Saumya [National Renewable Energy Laborator↗
DOE OSTI2023

An African-Specific Variant of TP5 3 Reveals PADI4 as a Regulator of p53-Mediated Tumor Suppression

TP53 is the most frequently mutated gene in cancer, yet key target genes for p53-mediated tumor suppression remain unidentified. Here, we characterize a rare, African-specific germline variant of TP53 in the DNA-binding domain Tyr107His (Y107H). Nuclear magnetic resonance and crystal structures reveal that Y107H is structurally similar to wild-type p53. Consistent with this, we find that Y107H can suppress tumor colony formation and is impaired for the transactivation of only a small subset of p53 target genes; this includes the epigenetic modifier PADI4, which deiminates arginine to the nonnatural amino acid citrulline. Surprisingly, we show that Y107H mice develop spontaneous cancers and metastases and that Y107H shows impaired tumor suppression in two other models. We show that PADI4 is itself tumor suppressive and that it requires an intact immune system for tumor suppression. We identify a p53–PADI4 gene signature that is predictive of survival and the efficacy of immune-checkpoint inhibitors.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Observations of Boundary Layer Convergence Lines and Associated Updrafts in the U.S. Southern Great Plains

Abstract Boundary layer convergence lines (CLs) are highly effective at deep-convection initiation (DCI), suggesting that their associated updraft properties differ from those of more widespread turbulent updrafts in the planetary boundary layer (PBL). This study exploits observations at the Atmospheric Radiation Measurement Southern Great Plains (ARM SGP) observatory in Oklahoma from 2011 to 2016 to quantify CL properties and their relation to turbulent PBL eddies preceding CL arrival. Two independent methods for estimating CL properties are developed at two locations in the SGP region, both relying on the assumption of a 2D circulation in the CL-normal plane but using different combinations of instruments. The first (the radar method) relies mainly on scanning radar data and is applied to 61 CLs passing near a high-resolution scanning radar based in Nardin, Oklahoma, while the second (the surface method) relies mainly on surface wind data and is applied to 68 CLs crossing the SGP facility in nearby Lamont, Oklahoma. Mean daytime (1000–1900 LST) CL width (∼2 km) and convergence magnitude (∼0.003 s −1 ) are similar for both methods, and mean daytime CL depth is ∼0.75 km. The two methods disagree at night (0000–1000 and 1900–2400 LST), where the surface method estimates wider and weaker CLs than the radar method. This difference may stem from the radar beam overshooting the shallow, highly stable nocturnal PBL. The largest CL updrafts are slightly wider (∼20%) and stronger (∼40%) than the largest PBL updrafts in the pre-CL period, generating 50%–100% larger updraft mass fluxes over most of the PBL depth. Significance Statement Deep convection is commonly initiated by boundary layer convergence lines (CLs), which are associated with intense surface-based wind convergence and strong updrafts that may lift air to saturation. Although CLs form regularly, they are far less common than ordinary, short-lived turbulent thermals in the daytime boundary layer. To better understand why CLs are so effective at deep-convection initiation, we observationally quantify their morphologies and strengths and compare these properties to those of surrounding turbulent updrafts. Perhaps surprisingly, the CLs are found to exhibit only slightly larger scales and strengths as the turbulent updrafts. Although these marginal increases help to explain the preference for storms to initiate along CLs, they likely are not the whole story.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Observational Study of the Thermodynamics and Morphological Characteristics of a Midlatitude Continental Cold Pool Event

Abstract Convectively generated cold pools are important to the Earth system as they exert strong controls on deep convective-storm initiation, intensity, and life cycle. Despite their importance, efforts to introduce such cold pool controls into weather and climate models lack guidance and/or physical constraints from cold pool observations. This work presents a detailed, purely observational analysis of a cold pool event that took place on 23–24 May 2011 in north-central Oklahoma. The characteristics of the cold pool, and the spatiotemporal evolution of the hydrometeors and dynamics in the proximity of the cold pool, are studied with high-resolution observations. The unprecedented dataset used in this work to study cold pool characteristics includes an enhanced network of surface weather stations, a high-temporal-frequency sounding array, and the NEXRAD and Atmospheric Radiation Measurement (ARM) Southern Great Plains radar networks. The potential use of NEXRAD surveillance scans to estimate height and propagation speed of the leading edge of the cold pool (LECP) is presented in this work. Manual identification and tracking of the LECP from NEXRAD imagery shows a spatial and temporal heterogeneity of the LECP properties. Surprisingly, over its detected life cycle, the LECP speed remains almost constant, even though the strength of the cold pool diminishes in time and its height varies. Radar analysis shows that pulses of graupel and hail within downdrafts in the convective system generating the cold pool appeared to be related to temporary increases in the LECP height.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

TECHNOLOGY: A Lesson In LED Adoption: Understanding the hurdles faced by K–12 schools

PK-12 schools lag in upgrading fluorescent lighting. Surprised? So were we; spurring a journey to understand the reasons for lagging adoption of LED. During conversations with school facility managers and other lighting professionals the reasons became clearer. What follows is a synopsis of what has been uncovered so far, yet there remains much to learn. Here, these stories are not the product of imagination; they represent real experiences, real decisions, and real concerns from 9 school districts in 7 states from coast to coast.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Visualization at exascale: Making it all work with VTK-m

The VTK-m software library enables scientific visualization on exascale-class supercomputers. Exascale machines are particularly challenging for software development in part because they use GPU accelerators to provide the vast majority of their computational throughput. Algorithmic designs for GPUs and GPU-centric computing often deviate from those that worked well on previous generations of high-performance computers that relied on traditional CPUs. Fortunately, VTK-m provides scientific visualization algorithms for GPUs and other accelerators. VTK-m also provides a framework that simplifies the implementation of new algorithms and adds a porting layer to work across multiple processor types. This paper describes the main challenges encountered when making scientific visualization available at exascale. Here, we document the surprises and obstacles faced when moving from pre-exascale platforms to the final exascale designs and the performance on those systems including scaling studies on Frontier, an exascale machine with over 37,000 AMD GPUs. We also report on the integration of VTK-m with other exascale software technologies. Finally, we show how VTK-m helps scientific discovery for applications such as fusion and particle acceleration that leverage an exascale supercomputer.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

New perspectives on butyrate assimilation in Rhodospirillum rubrum S1H under photoheterotrophic conditions

Background: The great metabolic versatility of the purple non-sulfur bacteria is of particular interest in green technology. Rhodospirillum rubrum S1H is an α-proteobacterium that is capable of photoheterotrophic assimilation of volatile fatty acids (VFAs). Butyrate is one of the most abundant VFAs produced during fermentative biodegradation of crude organic wastes in various applications. While there is a growing understanding of the photoassimilation of acetate, another abundantly produced VFA, the mechanisms involved in the photoheterotrophic metabolism of butyrate remain poorly studied. Results: In this work, we used proteomic and functional genomic analyses to determine potential metabolic pathways involved in the photoassimilation of butyrate. We propose that a fraction of butyrate is converted to acetyl-CoA, a reaction shared with polyhydroxybutyrate metabolism, while the other fraction supplies the ethylmalonyl-CoA (EMC) pathway used as an anaplerotic pathway to replenish the TCA cycle. Surprisingly, we also highlighted a potential assimilation pathway, through isoleucine synthesis and degradation, allowing the conversion of acetyl-CoA to propionyl-CoA. We tentatively named this pathway the methylbutanoyl-CoA pathway (MBC). An increase in isoleucine abundance was observed during the early growth phase under butyrate condition. Nevertheless, while the EMC and MBC pathways appeared to be concomitantly used, a genome-wide mutant fitness assay highlighted the EMC pathway as the only pathway strictly required for the assimilation of butyrate. Conclusion: Photoheterotrophic growth of Rs. rubrum with butyrate as sole carbon source requires a functional EMC pathway. In addition, a new assimilation pathway involving isoleucine synthesis and degradation, named the methylbutanoyl-CoA (MBC) pathway, could also be involved in the assimilation of this volatile fatty acid by Rs. rubrum.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Metabolic engineering of Rhodotorula toruloides IFO0880 improves C16 and C18 fatty alcohol production from synthetic media

Abstract Background The oleaginous, carotenogenic yeast Rhodotorula toruloides has been increasingly explored as a platform organism for the production of terpenoids and fatty acid derivatives. Fatty alcohols, a fatty acid derivative widely used in the production of detergents and surfactants, can be produced microbially with the expression of a heterologous fatty acyl-CoA reductase. Due to its high lipid production, R. toruloides has high potential for fatty alcohol production, and in this study several metabolic engineering approaches were investigated to improve the titer of this product. Results Fatty acyl-CoA reductase from Marinobacter aqueolei was co-expressed with SpCas9 in R. toruloides IFO0880 and a panel of gene overexpressions and Cas9-mediated gene deletions were explored to increase the fatty alcohol production. Two overexpression targets ( ACL1 and ACC1 , improving cytosolic acetyl-CoA and malonyl-CoA production, respectively) and two deletion targets (the acyltransferases DGA1 and LRO1 ) resulted in significant (1.8 to 4.4-fold) increases to the fatty alcohol titer in culture tubes. Combinatorial exploration of these modifications in bioreactor fermentation culminated in a 3.7 g/L fatty alcohol titer in the LRO1 Δ mutant. As LRO1 deletion was not found to be beneficial for fatty alcohol production in other yeasts, a lipidomic comparison of the DGA1 and LRO1 knockout mutants was performed, finding that DGA1 is the primary acyltransferase responsible for triacylglyceride production in R. toruloides , while LRO1 disruption simultaneously improved fatty alcohol production, increased diacylglyceride and triacylglyceride production, and increased glucose consumption. Conclusions The fatty alcohol titer of fatty acyl-CoA reductase-expressing R. toruloides was significantly improved through the deletion of LRO1 , or the deletion of DGA1 combined with overexpression of ACC1 and ACL1 . Disruption of LRO1 surprisingly increased both lipid and fatty alcohol production, creating a possible avenue for future study of the lipid metabolism of this yeast.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Nitrogen starvation causes lipid remodeling in Rhodotorula toruloides

Abstract Background The oleaginous yeast Rhodotorula toruloides is a promising chassis organism for the biomanufacturing of value-added bioproducts. It can accumulate lipids at a high fraction of biomass. However, metabolic engineering efforts in this organism have progressed at a slower pace than those in more extensively studied yeasts. Few studies have investigated the lipid accumulation phenotype exhibited by R. toruloides under nitrogen limitation conditions. Consequently, there have been only a few studies exploiting the lipid metabolism for higher product titers. Results We performed a multi-omic investigation of the lipid accumulation phenotype under nitrogen limitation. Specifically, we performed comparative transcriptomic and lipidomic analysis of the oleaginous yeast under nitrogen-sufficient and nitrogen deficient conditions. Clustering analysis of transcriptomic data was used to identify the growth phase where nitrogen-deficient cultures diverged from the baseline conditions. Independently, lipidomic data was used to identify that lipid fractions shifted from mostly phospholipids to mostly storage lipids under the nitrogen-deficient phenotype. Through an integrative lens of transcriptomic and lipidomic analysis, we discovered that R. toruloides undergoes lipid remodeling during nitrogen limitation, wherein the pool of phospholipids gets remodeled to mostly storage lipids. We identify specific mRNAs and pathways that are strongly correlated with an increase in lipid levels, thus identifying putative targets for engineering greater lipid accumulation in R. toruloides . One surprising pathway identified was related to inositol phosphate metabolism, suggesting further inquiry into its role in lipid accumulation. Conclusions Integrative analysis identified the specific biosynthetic pathways that are differentially regulated during lipid remodeling. This insight into the mechanisms of lipid accumulation can lead to the success of future metabolic engineering strategies for overproduction of oleochemicals.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Lipid membrane remodeling and metabolic response during isobutanol and ethanol exposure in Zymomonas mobilis

Abstract Background Recent engineering efforts have targeted the ethanologenic bacterium Zymomonas mobilis for isobutanol production. However, significant hurdles remain due this organism’s vulnerability to isobutanol toxicity, adversely affecting its growth and productivity. The limited understanding of the physiological impacts of isobutanol on Z. mobilis constrains our ability to overcome these production barriers. Results We utilized a systems-level approach comprising LC–MS/MS-based lipidomics, metabolomics, and shotgun proteomics, to investigate how exposure to ethanol and isobutanol impact the lipid membrane composition and overall physiology of Z. mobilis . Our analysis revealed significant and distinct alterations in membrane phospholipid and fatty acid composition resulting from ethanol and isobutanol exposure. Notably, ethanol exposure increased membrane cyclopropane fatty acid content and expression of cyclopropane fatty acid (CFA) synthase. Surprisingly, isobutanol decreased cyclopropane fatty acid content despite robust upregulation of CFA synthase. Overexpression of the native Z. mobilis’ CFA synthase increased cyclopropane fatty acid content in all phospholipid classes and was associated with a significant improvement in growth rates in the presence of added ethanol and isobutanol. Heterologous expression of CFA synthase from Clostridium acetobutylicum resulted in a near complete replacement of unsaturated fatty acids with cyclopropane fatty acids, affecting all lipid classes. However, this did not translate to improved growth rates under isobutanol exposure. Correlating with its greater susceptibility to isobutanol, Z. mobilis exhibited more pronounced alterations in its proteome, metabolome, and overall cell morphology—including cell swelling and formation of intracellular protein aggregates —when exposed to isobutanol compared to ethanol. Isobutanol triggered a broad stress response marked by the upregulation of heat shock proteins, efflux transporters, DNA repair systems, and the downregulation of cell motility proteins. Isobutanol also elicited widespread dysregulation of Z. mobilis ’ primary metabolism evidenced by increased levels of nucleotide degradation intermediates and the depletion of biosynthetic and glycolytic intermediates. Conclusions This study provides a comprehensive, systems-level evaluation of the impact of ethanol and isobutanol exposure on the lipid membrane composition and overall physiology of Z. mobilis . These findings will guide engineering of Z. mobilis towards the creation of isobutanol-tolerant strains that can serve as robust platforms for the industrial production of isobutanol from lignocellulosic sugars.

09 BIOMASS FUELS↗
DOE OSTI2021

Deletion of a non-canonical regulatory sequence causes loss of Scn1a expression and epileptic phenotypes in mice

Abstract Background Genes with multiple co-active promoters appear common in brain, yet little is known about functional requirements for these potentially redundant genomic regulatory elements. SCN1A, which encodes the Na V 1.1 sodium channel alpha subunit, is one such gene with two co-active promoters. Mutations in SCN1A are associated with epilepsy, including Dravet syndrome (DS). The majority of DS patients harbor coding mutations causing SCN1A haploinsufficiency; however, putative causal non-coding promoter mutations have been identified. Methods To determine the functional role of one of these potentially redundant Scn1a promoters, we focused on the non-coding Scn1a 1b regulatory region, previously described as a non-canonical alternative transcriptional start site. We generated a transgenic mouse line with deletion of the extended evolutionarily conserved 1b non-coding interval and characterized changes in gene and protein expression, and assessed seizure activity and alterations in behavior. Results Mice harboring a deletion of the 1b non-coding interval exhibited surprisingly severe reductions of Scn1a and Na V 1.1 expression throughout the brain. This was accompanied by electroencephalographic and thermal-evoked seizures, and behavioral deficits. Conclusions This work contributes to functional dissection of the regulatory wiring of a major epilepsy risk gene, SCN1A . We identified the 1b region as a critical disease-relevant regulatory element and provide evidence that non-canonical and seemingly redundant promoters can have essential function.

60 APPLIED LIFE SCIENCES↗