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At least 109 records · Page 6

Genetic and environmental variation impact the cuticular hydrocarbon metabolome on the stigmatic surfaces of maize

Abstract Background Simple non-isoprenoid hydrocarbons accumulate in discrete regions of the biosphere, including within bacteria and algae as a carbon and/or energy store, and the cuticles of plants and insects, where they may protect against environmental stresses. The extracellular cuticular surfaces of the stigmatic silks of maize are rich in linear hydrocarbons and therefore provide a convenient system to study the biological origins and functions of these unique metabolites. Results To test the hypotheses that genetics and environment influence the accumulation of surface hydrocarbons on silks and to examine the breadth of metabolome compositions across diverse germplasm, cuticular hydrocarbons were analyzed on husk-encased silks and silks that emerged from the husk leaves from 32 genetically diverse maize inbred lines, most of which are commonly utilized in genetics experiments. Total hydrocarbon accumulation varied ~ 10-fold among inbred lines, and up to 5-fold between emerged and husk-encased silks. Alkenes accounted for 5-60% of the total hydrocarbon metabolome, and the majority of alkenes were monoenes with a double bond at either the 7th or 9th carbon atom of the alkyl chain. Total hydrocarbon accumulation was impacted to similar degrees by genotype and husk encasement status, whereas genotype predominantly impacted alkene composition. Only minor differences in the metabolome were observed on silks that were emerged into the external environment for 3- versus 6-days. The environmental influence on the metabolome was further investigated by growing inbred lines in 2 years, one of which was warmer and wetter. Inbred lines grown in the drier year accumulated up to 2-fold more hydrocarbons and up to a 22% higher relative abundance of alkenes. In summary, the surface hydrocarbon metabolome of silks is primarily governed by genotype and husk encasement status, with smaller impacts of environment and genotype-by-environment interactions. Conclusions This study reveals that the composition of the cuticular hydrocarbon metabolome on silks is affected significantly by genetic factors, and is therefore amenable to dissection using quantitative genetic approaches. Such studies will clarify the genetic mechanisms responsible for the accumulation of these metabolites, enabling detailed functional investigations of the diverse and complex protective roles of silk surface lipids against environmental stresses.

Dennison, Tesia (ORCID:0000000340451175)↗

Genetic tools for engineering Zymomonas mobilis , Cereibacter sphaeroides and Novosphingobium aromaticivorans to improve production of bioenergy compounds

Limited genetic tools for non-model bacteria are one of the limiting factors for genetic studies. This review compiles genetic tools used for three non-model alpha-proteobacteria, such as Zymomonas mobilis, Cereibacter (Rhodobacter) sphaeroides, and Novosphingobium aromaticivorans, which hold significant potential to produce industrially essential bioenergy compounds due to their distinctive metabolic pathways and resilience in extreme environments. Each of these strains has a unique genetic profile that enables them to efficiently carry out key reactions relevant to producing bioenergy compounds, such as converting sugars into bioenergy compounds and breaking down lignotoxins. Genetic tools can further optimize these strains for enhanced bioenergy compound production. This review explores the metabolic advantages of these organisms. It highlights the available array of genetic toolkits that can be shared among them to unlock their full potential for sustainable biofuel production.

Biofuel↗

Methods for safely sharing dual-use genetic data

Background: Some genetic data has dual-use potential. Sharing pathogen data has shown tremendous value. For example therapeutic development and lineage tracking during the COVID pandemic. This data sharing is complicated by the fact that these data have the potential to be used for harm. The genome sequence of a pathogen can be used to enable malicious genetic engineering approaches or to recreate the pathogen from synthetic DNA. Standard data security methods can be applied to genetic data, but when data is shared between institutions, ensuring appropriate security can be difficult. Sensitive data that is shared internationally among a wide array of institutions can be especially difficult to control. Methods for securely storing and sharing genetic data with potential for dual-use are needed to mitigate this potential harm.Results: Here we propose new methods that allow genetic data to be shared in a data format that prevents a nefarious actor from accessing sensitive aspects of the data. Our methods obfuscate raw sequence data by pooling reads from different samples. This approach can ensure that data is secure while stored and during electronic transfer. We demonstrate that by pooling raw sequence data from multiple samples of the same organism, the ability to fully reconstruct any individual sample is prevented. In the pooled data, most genomic information remains, but reads or mutations cannot be directly attributed to any individual sample. To further restrict access to information, regions of a genome can be removed from the reads.Conclusion: Our methods obscure genomic information within raw sequence reads. This method can allow genetic data to be stored and shared while preventing a nefarious actor from being able to perfectly reconstruct an organism. Broad-scale sequence information remains, while fine scale details about specific samples are difficult or impossible to reconstruct. Our software is available at https://github.com/Geneinfosec-Inc/ReadMixer.

59 BASIC BIOLOGICAL SCIENCES↗

An investigation of messy genetic algorithms

Genetic algorithms (GAs) are search procedures based on the mechanics of natural selection and natural genetics. They combine the use of string codings or artificial chromosomes and populations with the selective and juxtapositional power of reproduction and recombination to motivate a surprisingly powerful search heuristic in many problems. Despite their empirical success, there has been a long standing objection to the use of GAs in arbitrarily difficult problems. A new approach was launched. Results to a 30-bit, order-three-deception problem were obtained using a new type of genetic algorithm called a messy genetic algorithm (mGAs). Messy genetic algorithms combine the use of variable-length strings, a two-phase selection scheme, and messy genetic operators to effect a solution to the fixed-coding problem of standard simple GAs. The results of the study of mGAs in problems with nonuniform subfunction scale and size are presented. The mGA approach is summarized, both its operation and the theory of its use. Experiments on problems of varying scale, varying building-block size, and combined varying scale and size are presented.

Goldberg, David E.↗

Problem solving with genetic algorithms and Splicer

Genetic algorithms are highly parallel, adaptive search procedures (i.e., problem-solving methods) loosely based on the processes of population genetics and Darwinian survival of the fittest. Genetic algorithms have proven useful in domains where other optimization techniques perform poorly. The main purpose of the paper is to discuss a NASA-sponsored software development project to develop a general-purpose tool for using genetic algorithms. The tool, called Splicer, can be used to solve a wide variety of optimization problems and is currently available from NASA and COSMIC. This discussion is preceded by an introduction to basic genetic algorithm concepts and a discussion of genetic algorithm applications.

Bayer, Steven E.↗

Optimization of laminated stacking sequence for buckling load maximization by genetic algorithm

The use of a genetic algorithm to optimize the stacking sequence of a composite laminate for buckling load maximization is studied. Various genetic parameters including the population size, the probability of mutation, and the probability of crossover are optimized by numerical experiments. A new genetic operator - permutation - is proposed and shown to be effective in reducing the cost of the genetic search. Results are obtained for a graphite-epoxy plate, first when only the buckling load is considered, and then when constraints on ply contiguity and strain failure are added. The influence on the genetic search of the penalty parameter enforcing the contiguity constraint is studied. The advantage of the genetic algorithm in producing several near-optimal designs is discussed.

Le Riche, Rodolphe↗

Temporal Dependence of Chromosomal Aberration on Radiation Quality and Cellular Genetic Background

Radiation induced cancer risks are driven by genetic instability. It is not well understood how different radiation sources induce genetic instability in cells with different genetic background. Here we report our studies on genetic instability, particularly chromosome instability using fluorescence in situ hybridization (FISH), in human primary lymphocytes, normal human fibroblasts, and transformed human mammary epithelial cells in a temporal manner after exposure to high energy protons and Fe ions. The chromosome spread was prepared 48 hours, 1 week, 2 week, and 1 month after radiation exposure. Chromosome aberrations were analyzed with whole chromosome specific probes (chr. 3 and chr. 6). After exposure to protons and Fe ions of similar cumulative energy (??), Fe ions induced more chromosomal aberrations at early time point (48 hours) in all three types of cells. Over time (after 1 month), more chromosome aberrations were observed in cells exposed to Fe ions than in the same type of cells exposed to protons. While the mammary epithelial cells have higher intrinsic genetic instability and higher rate of initial chromosome aberrations than the fibroblasts, the fibroblasts retained more chromosomal aberration after long term cell culture (1 month) in comparison to their initial frequency of chromosome aberration. In lymphocytes, the chromosome aberration frequency at 1 month after exposure to Fe ions was close to unexposed background, and the chromosome aberration frequency at 1 month after exposure to proton was much higher. In addition to human cells, mouse bone marrow cells isolated from strains CBA/CaH and C57BL/6 were irradiated with proton or Fe ions and were analyzed for chromosome aberration at different time points. Cells from CBA mice showed similar frequency of chromosome aberration at early and late time points, while cells from C57 mice showed very different chromosome aberration rate at early and late time points. Our results suggest that relative biological effectiveness (RBE) of radiation are different for different radiation sources, for different cell types, and for the same cell type with different genetic background at different times after radiation exposure. Caution must be taken in using RBE value to estimate biological effects from radiation exposure.

Lu, Tao↗

Lessons to be learned from a contentious challenge to mainstream radiobiological science (the linear no-threshold theory of genetic mutations)

There are both statistically valid and invalid reasons why scientists with differing default hypotheses can disagree in high-profile situations. Examples can be found in recent correspondence in this journal, which may offer lessons for resolving challenges to mainstream science, particularly when adherents of a minority view attempt to elevate the status of outlier studies and/or claim that self-interest explains the acceptance of the dominant theory. Edward J. Calabrese and I have been debating the historical origins of the linear no-threshold theory (LNT) of carcinogenesis and its use in the regulation of ionizing radiation. Professor Calabrese, a supporter of hormesis, has charged a committee of scientists with misconduct in their preparation of a 1956 report on the genetic effects of atomic radiation. Specifically he argues that the report mischaracterized the LNT research record and suppressed calculations of some committee members. After reviewing the available scientific literature, I found that the contemporaneous evidence overwhelmingly favored a (genetics) LNT and that no calculations were suppressed. Calabrese's claims about the scientific record do not hold up primarily because of lack of attention to statistical analysis. Ironically, outlier studies were more likely to favor supra-linearity, not sub-linearity. Finally, the claim of investigator bias, which underlies Calabrese's accusations about key studies, is based on misreading of text. Attention to ethics charges, early on, may help seed a counter narrative explaining the community's adoption of a default hypothesis and may help focus attention on valid evidence and any real weaknesses in the dominant paradigm. - Highlights: • Edward J Calabrese has made a contentious challenge to mainstream radiobiological science. • Such challenges should not be neglected, lest they enter the political arena without review. • Key genetic studies from the 1940s, challenged by Calabrese, were found consistent and unbiased. • A 1956 genetics report did not hide estimates and does not need investigation for misconduct. • The scientific record was strong for a no-threshold, linear genetic response to radiation.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Geographic patterns in morphometric and genetic variation for coyote populations with emphasis on southeastern coyotes

Prior to 1900, coyotes (Canis latrans) were restricted to the western and central regions of North America, but by the early 2000s, coyotes became ubiquitous throughout the eastern United States. Information regarding morphological and genetic structure of coyote populations in the southeastern United States is limited, and where data exist, they are rarely compared to those from other regions of North America. We assessed geographic patterns in morphology and genetics of coyotes with special consideration of coyotes in the southeastern United States. Mean body mass of coyote populations increased along a west-to-east gradient, with southeastern coyotes being intermediate to western and northeastern coyotes. Similarly, principal component analysis of body mass and linear body measurements suggested that southeastern coyotes were intermediate to western and northeastern coyotes in body size but exhibited shorter tails and ears from other populations. Genetic analyses indicated that southeastern coyotes represented a distinct genetic cluster that differentiated strongly from western and northeastern coyotes. We postulate that southeastern coyotes experienced lower immigration from western populations than did northeastern coyotes, and over time, genetically diverged from both western and northeastern populations. Coyotes colonizing eastern North America experienced different selective pressures than did stable populations in the core range, and we offer that the larger body size of eastern coyotes reflects an adaptation that improved dispersal capabilities of individuals in the expanding range.

59 BASIC BIOLOGICAL SCIENCES↗

Genetic algorithm optimization of nuclear criticality experiment for reduction of intermediate-energy 239 Pu nuclear data uncertainties

Nuclear criticality experiments are conducted to investigate specific nuclear data important for safe handling and storage of fissile materials, reactor design and operation, and the validation of radiation transport codes. Incorrect or uncertain nuclear data can prohibitively impact operational safety limits, reactor licensing, and predictive simulation capability; therefore, integral measurements from criticality experiments are necessary and should be performed frequently. To maximize the impact of the integral measurements, it is important to consider experiment geometry, material selection, and component dimensions. When taking these considerations into account, the experiment design process becomes iterative and very time intensive. This work utilizes a genetic algorithm to efficiently explore potential nuclear criticality experiment designs for the Laboratory Directed Research & Development project PARADIGM (PARallel Approach of Differential and InteGral Measurements) at Los Alamos National Laboratory. In this paper, the building blocks of the genetic algorithm are discussed in detail, the genetic algorithm methodology is verified, and the genetic algorithm is used to produce three candidate experiment models for the final PARADIGM design. The three candidate models produced by the genetic algorithm consist of copper-reflected assemblies containing 14 repeating units of alumina, graphite, boron, and plutonium plates. Furthermore, in addition to the optimization results, final design considerations are also discussed for designs with a height and/or weight very close to or slightly above assembly machine operational limits.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Genetic Variants in CD44 and MAT1A Confer Susceptibility to Acute Skin Reaction in Breast Cancer Patients Undergoing Radiation Therapy

Purpose: Heterogeneity in radiation therapy (RT)-induced normal tissue toxicity is observed in 10% of cancer patients, limiting the therapeutic outcomes. In addition to treatment-related factors, normal tissue adverse reactions also manifest from genetic alterations in distinct pathways majorly involving DNA damage–repair genes, inflammatory cytokine genes, cell cycle regulation, and antioxidant response. Therefore, the common sequence variants in these radioresponsive genes might modify the severity of normal tissue toxicity, and the identification of the same could have clinical relevance as a predictive biomarker. Methods and Materials: The present study was conducted in a cohort of patients with breast cancer to evaluate the possible associations between genetic variants in radioresponsive genes described previously and the risk of developing RT-induced acute skin adverse reactions. We tested 22 genetic variants reported in 18 genes (ie, NFE2L2, OGG1, NEIL3, RAD17, PTTG1, REV3L, ALAD, CD44, RAD9A, TGFβR3, MAD2L2, MAP3K7, MAT1A, RPS6KB2, ZNF830, SH3GL1, BAX, and XRCC1) using TaqMan assay-based real-time polymerase chain reaction. At the end of RT, the severity of skin damage was scored, and the subjects were dichotomized as nonoverresponders (Radiation Therapy Oncology Group grade <2) and overresponders (Radiation Therapy Oncology Group grade ≥2) for analysis. Results: Of the 22 single nucleotide polymorphisms studied, the rs8193 polymorphism lying in the micro-RNA binding site of 3′-UTR of CD44 was significantly (P=.0270) associated with RT-induced adverse skin reactions. Generalized multifactor dimensionality reduction analysis showed significant (P=.0107) gene–gene interactions between MAT1A and CD44. Furthermore, an increase in the total number of risk alleles was associated with increasing occurrence of overresponses (P=.0302). Conclusions: The genetic polymorphisms in radioresponsive genes act as genetic modifiers of acute normal tissue toxicity outcomes after RT by acting individually (rs8193), by gene–gene interactions (MAT1A and CD44), and/or by the additive effects of risk alleles.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Construction of genetic logic gates based on the T7 RNA polymerase expression system in Rhodococcus opacus PD630

Rhodococcus opacus PD630 (R. opacus) is a non-model, gram-positive bacterium which holds promise as a biological catalyst for the conversion of lignocellulosic biomass into value-added products. In particular, it demonstrates both a high tolerance for and an ability to consume inhibitory lignin-derived aromatics, generates large quantities of lipids, exhibits a relatively rapid growth rate, and has a growing genetic toolbox for engineering. Yet, the availability of genetic parts for tunable, high-activity gene expression is still limited in R. opacus. Moreover, genetic logic circuits for sophisticated gene regulation have never been demonstrated in Rhodococcus spp. To address these shortcomings, two inducible T7 RNA polymerase-based expression systems were implemented for the first time in R. opacus and applied to constructing AND and NAND genetic logic gates. Additionally, three IPTG-inducible promoters were created by inserting LacI binding sites into newly-characterized constitutive promoters. Furthermore, four novel aromatic sensors for 4-hydroxybenzoic acid, vanillic acid, sodium benzoate, and guaiacol were developed, expanding the gene expression toolbox. Lastly, the T7 RNA polymerase platform was combined with a synthetic IPTG-inducible promoter to create an IMPLY logic gate. Overall, this work represents the first demonstration of a heterologous RNA polymerase system and synthetic genetic logic in R. opacus, enabling complex and tunable gene regulation in this promising non-model host for bioproduction.

59 BASIC BIOLOGICAL SCIENCES↗

Quantitative characterization of genetic parts and circuits for plant synthetic biology

Plant synthetic biology promises immense technological benefits and hopes of developing a sustainable bio-based economy. Synthetic biology enables predictive design of synthetic genetic networks based on quantitatively characterized standardized genetic parts. This presents a significant practical barrier since stable transformation of plants is very time consuming, especially when testing large numbers of components. An attractive alternative is the use of transient protoplast assays. We describe a method for rapid quantitative characterization of genetic components in Arabidopsis thaliana, using plant protoplasts and dual luciferase outputs. Here we found that transient protoplast assays are marked by significant experimental variability. We developed a mathematical model to describe, and statistical normalization methods to account for this variability, allowing us to extract quantitative parameters. Over 120 synthetic genetic components were built and characterized using our Arabidopsis protoplasts quantitative testing platform. We validate our method by comparing transient expression of genetic components with stably transformed plants.

59 BASIC BIOLOGICAL SCIENCES↗

Identification of genetic factors that modify motor performance and body weight using Collaborative Cross mice

Evidence has emerged that suggests a link between motor deficits, obesity and many neurological disorders. However, the contributing genetic risk factors are poorly understood. Here we used the Collaborative Cross (CC), a large panel of newly inbred mice that captures 90% of the known variation among laboratory mice, to identify the genetic loci controlling rotarod performance and its relationship with body weight in a cohort of 365 mice across 16 CC strains. Body weight and rotarod performance varied widely across CC strains and were significantly negatively correlated. Genetic linkage analysis identified 14 loci that were associated with body weight. However, 45 loci affected rotarod performance, seven of which were also associated with body weight, suggesting a strong link at the genetic level. As a result, we show that genes identified in this study overlap significantly with those related to neurological disorders and obesity found in human GWA studies. In conclusion, our results provide a genetic framework for studies of the connection between body weight, the central nervous system and behavior.

59 BASIC BIOLOGICAL SCIENCES↗

Correlational selection and genetic architecture shape the evolution of the leaf economics spectrum in a perennial grass

The generality of the worldwide leaf economics spectrum (LES) has made it a pillar of trait-based ecological research. Yet, few studies have examined the processes shaping the evolution of the LES within species, in part, because most species occupy only a small portion of the LES. Here, to address this gap, we took advantage of the distinct leaf economics strategies present in different ecotypes of the phenotypically diverse perennial grass Panicum virgatum (switchgrass) to generate a genetic mapping population, which we planted in common gardens at three sites spanning 12 degrees of latitude in the central United States. With this genetic mapping population, we evaluated two potentially interacting causes of LES evolution: 1) genetic architecture, where multiple traits are influenced by either the same gene (pleiotropy) or by genes in close physical proximity (genetic linkage), and 2) correlational selection, where selection acts on traits in combination rather than in isolation. We found that shared genetic architecture influenced covariation between photosynthetic rate (A MASS ) and leaf nitrogen (N MASS ) and between A MASS and leaf mass per area (LMA). We also found that correlational selection favored the trait combinations predicted by the LES (e.g., high LMA with low N MASS or low LMA with high N MASS ) and disfavored other, mismatched trait combinations at two of the three sites. Together, these results demonstrate how the evolution of an integrated LES within species can arise from multiple evolutionary causes.

59 BASIC BIOLOGICAL SCIENCES↗

Genetic characterization of a Sorghum bicolor multiparent mapping population emphasizing carbon-partitioning dynamics

Sorghum bicolor, a photosynthetically efficient C4 grass, represents an important source of grain, forage, fermentable sugars, and cellulosic fibers that can be utilized in myriad applications ranging from bioenergy to bioindustrial feedstocks. Sorghum’s efficient fixation of carbon per unit time per unit area per unit input has led to its classification as a preferred biomass crop highlighted by its designation as an advanced biofuel by the U.S. Department of Energy. Due to its extensive genetic diversity and worldwide colonization, sorghum has considerable diversity for a range of phenotypes influencing productivity, composition, and sink/source dynamics. To dissect the genetic basis of these key traits, we present a sorghum carbon-partitioning nested association mapping (NAM) population generated by crossing 11 diverse founder lines with Grassl as the single recurrent female. By exploiting existing variation among cellulosic, forage, sweet, and grain sorghum carbon partitioning regimes, the sorghum carbon-partitioning NAM population will allow the identification of important biomass-associated traits, elucidate the genetic architecture underlying carbon partitioning and improve our understanding of the genetic determinants affecting unique phenotypes within Poaceae. We contrast this NAM population with an existing grain population generated using Tx430 as the recurrent female. Genotypic data are assessed for quality by examining variant density, nucleotide diversity, linkage decay, and are validated using pericarp and testa phenotypes to map known genes affecting these phenotypes. We release the 11-family NAM population along with corresponding genomic data for use in genetic, genomic, and agronomic studies with a focus on carbon-partitioning regimes.

multiparental populations↗

Exploring genetic diversity, population structure, and subgenome differences in the allopolyploid Camelina sativa : implications for future breeding and research studies

Abstract Camelina (Camelina sativa), an allohexaploid species, is an emerging aviation biofuel crop that has been the focus of resurgent interest in recent decades. To guide future breeding and crop improvement efforts, the community requires a deeper comprehension of subgenome dominance, often noted in allopolyploid species, “alongside an understanding of the genetic diversity” and population structure of material present within breeding programs. We conducted population genetic analyses of a C. sativa diversity panel, leveraging a new genome, to estimate nucleotide diversity and population structure, and analyzed for patterns of subgenome expression dominance among different organs. Our analyses confirm that C. sativa has relatively low genetic diversity and show that the SG3 subgenome has substantially lower genetic diversity compared to the other two subgenomes. Despite the low genetic diversity, our analyses identified 13 distinct subpopulations including two distinct wild populations and others putatively representing founders in existing breeding populations. When analyzing for subgenome composition of long non-coding RNAs, which are known to play important roles in (a)biotic stress tolerance, we found that the SG3 subgenome contained significantly more lincRNAs compared to other subgenomes. Similarly, transcriptome analyses revealed that expression dominance of SG3 is not as strong as previously reported and may not be universal across all organ types. From a global analysis, SG3 “was only significant higher expressed” in flower, flower bud, and fruit organs, which is an important discovery given that the crop yield is associated with these organs. Collectively, these results will be valuable for guiding future breeding efforts in camelina.

Agriculture↗

From quantitative trait loci towards mechanisms: Linkage Integration Hypothesis Testing (LIgHT) sheds light on the mechanisms of genetically modulated stress tolerance

The goal of this work is to assess the mechanistic bases of natural genetic variations in plant responses of photosynthesis to stress. To achieve this goal, we devised the Linkage Integration Hypothesis Testing (LIgHT) approach, comparing chromosomal locations of quantitative trait loci (QTLs) for multiple phenotypes to distinguish between hypothetical mechanisms. As a use case, we explored genetic variations in photosynthesis-related processes under chilling stress in recombinant inbred lines of cowpea ( Vigna unguiculata L. Walp.). We focused on photosynthesis-related parameters measurable in high throughput and indicative of proposed chilling responses, including the states of PSI and PSII, photoprotective non-photochemical quenching, PSII photodamage, and nyctinastic leaf movements (NLMs). The patterns of QTL linkages indicated that chilling stress tolerance is genetically controlled by avoiding PSII photodamage rather than PSI damage or NLMs. This model was validated in a separate experiment measuring the rates of PSII photodamage and repair. Additional linkages suggest that chilling-induced damage to PSII is controlled by the thylakoid proton motive force and redox state of PSII. This regulation appears to be modulated by thylakoid fatty acid composition, previously associated with the same genetic loci and now supported by broader mechanistic evidence. We propose that the LIgHT approach can be broadly applied to test mechanisms underlying genetic variations.

MultispeQ↗