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The availability of well-assembled genome sequences and reduced sequencing costs have enabled the resequencing of many additional accessions in several crops, thus facilitating the rapid discovery and development of simple sequence repeat (SSR) markers. Although the genome sequence of inbred spinach line Sp75 is available, previous efforts have resulted in a limited number of useful SSR markers. Identification of additional polymorphic SSR markers will support genetics and breeding research in spinach. This study aimed to use the available genomic resources to mine and catalog a large number of polymorphic SSR markers. A search for SSR loci on six chromosome sequences of spinach line Sp75 using GMATA identified a total of 42,155 loci with repeat motifs of two to six nucleotides in the Sp75 reference genome. Whole-genome sequences (30x) of additional 21 accessions were aligned against the chromosome sequences of the reference genome and in silico genotyped using the HipSTR program by comparing and counting repeat numbers variation across the SSR loci among the accessions. The HipSTR program generated SSR genotype data were filtered for monomorphic and high missing loci, and a final set of the 5986 polymorphic SSR loci were identified. The polymorphic SSR loci were present at a density of 12.9 SSRs/Mb and were physically mapped. Out of 36 randomly selected SSR loci for validation, two failed to amplify, while the remaining were all polymorphic in a set of 48 spinach accessions from 34 countries. Genetic diversity analysis performed using the SSRs allele score data on the 48 spinach accessions showed three main population groups. This strategy to mine and develop polymorphic SSR markers by a comparative analysis of the genome sequences of multiple accessions and computational genotyping of the candidate SSR loci eliminates the need for laborious experimental screening. Our approach increased the efficiency of discovering a large set of novel polymorphic SSR markers, as demonstrated in this report.

A major bottleneck in identifying therapies to control citrus greening and other devastating plant diseases caused by fastidious pathogens is our inability to culture the pathogens in defined media or axenic cultures. As such, conventional approaches for antimicrobial evaluation (genetic or chemical) rely on time-consuming, low-throughput and inherently variable whole-plant assays. Here, we report that plant hairy roots support the growth of fastidious pathogens like Candidatus Liberibacter spp., the presumptive causal agents of citrus greening, potato zebra chip and tomato vein greening diseases. Importantly, we leverage the microbial hairy roots for rapid, reproducible efficacy screening of multiple therapies. We identify six antimicrobial peptides, two plant immune regulators and eight chemicals which inhibit Candidatus Liberibacter spp. in plant tissues. The antimicrobials, either singly or in combination, can be used as near- and long-term therapies to control citrus greening, potato zebra chip and tomato vein greening diseases. The putative causal agent of citrus greening Candidatus Liberibacter asiaticus ( C Las) cannot be cultured, which hampers finding new therapies to control this devastating disease. Here, the authors show that hairy roots support C Las propagation and enable high throughput antimicrobial screening.

Vitamin C (VC), also known as ascorbic acid and ascorbate, is a water-soluble antioxidant in plants that promotes skin health and immune function in humans. Spinach ( Spinacia oleracea L.) is a leafy green widely consumed for its health benefits. Recent reports have shown that nutritional content, including VC, can be improved in spinach. However, due to its complex inheritance, new selection methods are needed to improve selection for cultivar development. In this study, single nucleotide polymorphism (SNP) markers identified by genome-wide association (GWAS) were used for genomic prediction (GP) to improve prediction accuracy (PA) for VC content in spinach. A set of 147,977 SNPs generated from whole genome resequencing was used for GWAS in a panel of 347 spinach genotypes by six GWAS models. Sixty-two SNP markers distributed on all six spinach chromosomes were associated with VC content. PA for the selection of VC content was estimated with fourteen random SNP sets across seven GP models. The results indicated that the PA can be > 40% after using 1,000 or more SNPs in six of the seven models tested; using GWAS-derived significant SNP markers PA increases to a high r -value up to 0.7 when using 62 associated SNP markers in Bayes ridge regression (BRR) model. Upon validation, identified accessions with high VC and high PA genomic selection model can be used in spinach breeding programs to develop high VC content cultivars.

The efficient acquisition and transport of nutrients by plants largely depend on the root architecture. Due to the absence of complex microbial network interactions and soil heterogeneity in a restricted soilless medium, the architecture of roots is a function of genetics defined by the soilless matrix and exogenously supplied nutrients such as nitrogen (N). The knowledge of root trait combinations that offer the optimal nitrogen use efficiency (NUE) is far from being conclusive. The objective of this study was to define the root trait(s) that best predicts and correlates with vegetative biomass under differed N treatments. We used eight image-derived root architectural traits of 202 diverse spinach lines grown in two N concentrations (high N, HN, and low N, LN) in randomized complete blocks design. Supervised random forest (RF) machine learning augmented by ranger hyperparameter grid search was used to predict the variable importance of the root traits. We also determined the broad-sense heritability (H) and genetic ( r g ) and phenotypic ( r p ) correlations between root traits and the vegetative biomass (shoot weight, SWt). Each root trait was assigned a predicted importance rank based on the trait’s contribution to the cumulative reduction in the mean square error (MSE) in the RF tree regression models for SWt. The root traits were further prioritized for potential selection based on the r g and SWt correlated response (CR). The predicted importance of the eight root traits showed that the number of root tips (Tips) and root length (RLength) under HN and crossings (Xsings) and root average diameter (RAvdiam) under LN were the most relevant. SWt had a highly antagonistic r g (− 0.83) to RAvdiam, but a high predicted indirect selection efficiency (− 112.8%) with RAvdiam under LN; RAvdiam showed no significant rg or rp to SWt under HN. In limited N availability, we suggest that selecting against larger RAvdiam as a secondary trait might improve biomass and, hence, NUE with no apparent yield penalty under HN.

This study addresses the challenge of optimizing flat-plate solar collector design, traditionally reliant on trial-and-error and simplified engineering design methods. We propose using physics-informed neural networks (PINNs) to predict optimal design conditions in a range of data that not only characterized the highlands of Ecuador but also similar geographical locations. The model integrates three interconnected neural networks to predict global collector efficiency by considering atmospheric, geometric, and physical variables, including overall loss coefficient, efficiency factors, outlet fluid temperature, and useful heat gain. The PINNs model surpasses traditional simplified thermodynamic equations employed in engineering design by effectively integrating thermodynamic principles with data-driven insights, offering more accurate modeling of nonlinear phenomena. This approach enhances the precision of solar collector performance predictions, making it particularly valuable for optimizing designs in Ecuador’s highlands and similar regions with unique climatic conditions. The ANN predicted a collector overall loss coefficient of 5.199 W/(m2·K), closely matching the thermodynamic model’s 5.189 W/(m2·K), with similar accuracy in collector useful energy gain (722.85 W) and global collector efficiency (33.68%). Although the PINNs model showed minor discrepancies in certain parameters, it outperformed traditional methods in capturing the complex, nonlinear behavior of the data set, especially in predicting outlet fluid temperature (55.05 °C vs. 67.22 °C).

Use of high-throughput sequencing (HTS) has become indispensable in life science research. Raw HTS data contains several sequencing artifacts, and as a first step it is imperative to remove the artifacts for reliable downstream bioinformatics analysis. Although there are multiple stand-alone tools available that can perform the various quality control steps separately, availability of an integrated tool that can allow one-step, automated quality control analysis of HTS datasets will significantly enhance handling large number of samples parallelly. Here, we developed HTSQualC, a stand-alone, flexible, and easy-to-use software for one-step quality control analysis of raw HTS data. HTSQualC can evaluate HTS data quality and perform filtering and trimming analysis in a single run. We evaluated the performance of HTSQualC for conducting batch analysis of HTS datasets with 322 samples with an average ~ 1 M (paired end) sequence reads per sample. HTSQualC accomplished the QC analysis in ~ 3 h in distributed mode and ~ 31 h in shared mode, thus underscoring its utility and robust performance. In addition to command-line execution, we integrated HTSQualC into the free, open-source, CyVerse cyberinfrastructure resource as a GUI interface, for wider access to experimental biologists who have limited computational resources and/or programming abilities.

O artigo examina a ascensão e a queda da empresa Engesa-Engenheiros Especializados, especialmente entre 1974 e 1990. O artigo é resultado de pesquisa com fontes documentais recentemente desclassificadas pelo Arquivo Nacional. A documentação consultada sugere que, na fase de ascensão, a Engesa foi impulsionada por uma eficiente vinculação entre indústria de defesa, exportação de armamento e política externa brasileira, principalmente durante os governos burocrático-autoritários de Ernesto Geisel e João Figueiredo. Entretanto, fragilidades financeiras e administrativas, junto a uma infrutuosa e dispendiosa tentativa de salto tecnológico, acabaram colocando a empresa em uma situação insustentável, conduzindo finalmente à sua queda e falência no início da década de 1990. A experiência da Engesa constitui um exemplo significativo nas pesquisas sobre inovação tecnológica, estudos estratégicos e relações internacionais. The article examines the rise and fall of the firm Engesa-Engenheiros Especializados, especially between 1974 and 1990. The article is the result of research with documentary sources recently declassified by the National Archives. The consulted documentation suggests that, in its ascendant phase, Engesa was driven by an efficient link between the defense industry, arms exports, and Brazilian foreign policy, mainly during the bureaucratic-authoritarian governments of Ernesto Geisel and João Figueiredo. However, financial and administrative weaknesses, along with an unsuccessful and costly attempt to make a technological leap, put the firm in an unsustainable situation, finally leading to its fall and bankruptcy in the early 1990s. Engesa’s experience is a paradigmatic example in studies of technological innovation, strategic research, and international relations.

The consumption of sugar-sweetened beverages (SSBs), which can lead to weight gain, is rising in middle-income countries (MICs). Taxing SSBs may help address this challenge. Systematic reviews focused on high-income countries indicate that taxing SSBs may reduce SSB consumption. Responsiveness to price changes may differ in MICs, where governments are considering the tax. To help inform their policy decisions, this review compiles evidence from MICs, assessing post-tax price increases (objective 1), changes in demand for SSBs and other products, overall and by socio-economic groups (objective 2), and effects on overweight and obesity prevalence (objective 3). We conducted a systematic review on the effectiveness of SSB taxation in MICs (1990-2016) and identified nine studies from Brazil, Ecuador, India, Mexico, Peru, and South Africa. Estimates for own-price elasticity ranged from -0.6 to -1.2, and decreases in SSB consumption ranged from 5 to 39 kilojoules per person per day given a 10% increase in SSB prices. The review found that milk is a likely substitute, and foods prepared away from home, snacks, and candy are likely complements to SSBs. A quasi-experimental study and two modeling studies also found a negative relationship between SSB prices and obesity outcomes after accounting for substitution effects. Estimates are consistent despite variation in baseline obesity prevalence and per person per day consumption of SSBs across countries studied. The review indicates that taxing SSBs will increase the prices of SSBs, especially sugary soda, in markets with few producers. Taxing SSBs will also reduce net energy intake by enough to prevent further growth in obesity prevalence, but not to reduce population weight permanently. Additional research using better survey data and stronger study designs is needed to ascertain the long-term effectiveness of an SSB tax on obesity prevalence in MICs.

Ethylene response factors (ERFs) comprise a large family of transcription factors that regulate numerous biological processes including growth, development, and response to environmental stresses. Here, we report that Pti5, an ERF in tomato [Solanum lycopersicum (Linnaeus)] was transcriptionally upregulated in response to the potato aphid Macrosiphum euphorbiae (Thomas), and contributed to plant defences that limited the population growth of this phloem-feeding insect. Virus-induced gene silencing of Pti5 enhanced aphid population growth on tomato, both on an aphid-susceptible cultivar and on a near-isogenic genotype that carried the Mi-1.2 resistance (R) gene. These results indicate that Pti5 contributes to basal resistance in susceptible plants and also can synergize with other R gene-mediated defences to limit aphid survival and reproduction. Although Pti5 contains the ERF motif, induction of this gene by aphids was independent of ethylene, since the ACC deaminase (ACD) transgene, which inhibits ethylene synthesis, did not diminish the responsiveness of Pti5 to aphid infestation. Furthermore, experiments with inhibitors of ethylene synthesis revealed that Pti5 and ethylene have distinctly different roles in plant responses to aphids. Whereas Pti5 contributed to antibiotic plant defences that limited aphid survival and reproduction on both resistant (Mi-1.2+) and susceptible (Mi-1.2−) genotypes, ethylene signalling promoted aphid infestation on susceptible plants but contributed to antixenotic defences that deterred the early stages of aphid host selection on resistant plants. These findings suggest that the antixenotic defences that inhibit aphid settling and the antibiotic defences that depress fecundity and promote mortality are regulated through different signalling pathways.