Academic literature on the topic 'Genomic data security'

AbstractThe DataBio’s agriculture pilots were carried out through a multi-actor whole-farm management approach using information technology, satellite positioning and remote sensing data as well as Internet of Things technology. The goal was to optimize the returns on inputs while reducing environmental impacts and streamlining the CAP monitoring. Novel knowledge was delivered for a more sustainable agriculture in line with the FAO call to achieve global food security and eliminate malnutrition for the more than nine billion people by 2050. The findings from the pilots shed light on the potential of digital agriculture to solve Europe’s concern of the declining workforce in the farming industry as the implemented technologies would help run farms with less workforce and manual labor. The pilot applications of big data technologies included autonomous machinery, mapping of yield, variable rate of applying agricultural inputs, input optimization, crop performance and in-season yields prediction as well as the genomic prediction and selection method allowing to cut cost and duration of cultivar development. The pilots showed their potential to transform agriculture, and the improved predictive analytics is expected to play a fundamental role in the production environment. As AI models are retrained with more data, the decision support systems become more accurate and serve the farmer better, leading to faster adoption. Adoption is further stimulated by cooperation between farmers to share investment costs and technological platforms allowing farmers to benchmark among themselves and across cropping season.

AbstractBecause Bacillus anthracis is one of the most lethal bioweapons, it is critical to create rapid, label-free screening and early warning systems to detect and classify anomalies in bacillus form vegetative cell and spore concentrations in the air. Even though significant effort has been invested in the development of various sensor solutions to detect, monitor, and identify airborne biological agents, no standard, interoperable, real-time or near-real-time optical sensor-based biothreat monitoring solution exists. Aside from the numerous advantages of genomic methods in microbe identification, optical sensors and microscopy-based technologies provide advantages in terms of rapid detection and classification capabilities. The AI-powered biothreat detection software platform from DataSenseLabs can perform intermethod comparison to cross-validate the results acquired by various quantitative phase imaging (QPI) measurement methodologies. This platform feature—support for multisensory data input—is not merely the foundation of the R&D level cross-validation approach, but also the key component of interoperable verification of air sample content in the case of airborne biothreat. Depending on the study design, sample type, and light microscopic or QPI measurement method, the platform’s algorithm system can detect and monitor abnormalities in the concentration of bacillus form objects taken from the air with greater than 80–95% accuracy. Another goal of the platform is to serve as a standardized tool for biomedical, environmental, and CBRN scientists to train and validate their concepts in pathogen detection and classification use cases, allowing them to better understand the gaps and challenges associated with artificial intelligence-powered optical sensor systems.

Original objectives: The long-term goal of the proposed research is to elucidate the transcription factors, genes and metabolic networks involved in carbon metabolism and partitioning in response to water deficit. The proposed research focuses on the GTLcalcium/calmodulinbindingTFs and the gene and metabolic networks modulated by these TFs in Arabidopsis thaliana. The specific objectives are as follows. Objective-1 (USA): Physiological analyses of GTL1 loss- and gain-of-function plants under water sufficient and drought stress conditions Objective 2 (USA / Israel-TAU): Characterizion of GTL target genes and bioinformatic analysis of data to eulcidate gene-network topology. Objective-3 (Israel-TAU): Regulation of GTLmediated transcription by Ca²⁺/calmodulin: mechanism and biological significance. Objective-4 (Israel-BGU): Metabolic networks and carbon partitioning in response to drought. Additional direction: In the course of the project we added another direction, which was reported in the 2nd annual report, to elucidate genes controlling drought avoidance. The TAU team has isolated a few unhydrotropic (hyd) mutants and are in the process of mapping these mutations (of hyd13 and hyd15; see last year's report for a description of these mutants under salt stress) in the Arabidopsis genome by map-based cloning and deep sequencing. For this purpose, each hyd mutant was crossed with a wild type plant of the Landsberg ecotype, and at the F2 stage, 500-700 seedlings showing the unhydrotropic phenotype were collected separately and pooled DNA samples were subkected to the Illumina deep sequencing technology. Bioinformatics were used to identify the exact genomic positions of the mutations (based on a comparison of the genomic sequences of the two Arabidopsis thaliana ecotypes (Columbia and Landsberg). Background: To feed the 9 billion people or more, expected to live on Earth by the mid 21st century, the production of high-quality food must increase substantially. Based on a 2009 Declaration of the World Summit on Food Security, a target of 70% more global food production by the year 2050 was marked, an unprecedented food-production growth rate. Importantly, due to the larger areas of low-yielding land globally, low-yielding environments offer the greatest opportunity for substantial increases in global food production. Nowadays, 70% of the global available water is used by agriculture, and 40% of the world food is produced from irrigated soils. Therefore, much needs to be done towards improving the efficiency of water use by plants, accompanied by increased crop yield production under water-limiting conditions. Major conclusions, solutions and achievements: We established that AtGTL1 (Arabidopsis thaliana GT-2 LIKE1) is a focal determinant in water deficit (drought) signaling and tolerance, and water use efficiency (WUE). The GTL1 transcription factor is an upstream regulator of stomatal development as a transrepressor of AtSDD1, which encodes a subtilisin protease that activates a MAP kinase pathway that negatively regulates stomatal lineage and density. GTL1 binds to the core GT3 cis-element in the SDD1 promoter and transrepresses its expression under water-sufficient conditions. GTL1 loss-of-function mutants have reduced stomatal number and transpiration, and enhanced drought tolerance and WUE. In this case, higher WUE under water sufficient conditions occurs without reduction in absolute biomass accumulation or carbon assimilation, indicating that gtl1-mediated effects on stomatal conductance and transpiration do not substantially affect CO₂ uptake. These results are proof-of-concept that fine-tuned regulation of stomatal density can result in drought tolerance and higher WUE with maintenance of yield stability. Implications: Accomplishments during the IS-4243-09R project provide unique tools for continued discovery research to enhance plant drought tolerance and WUE.

ABSTRACT Postharvest losses of fresh produce are estimated globally to be around 30%. Reducing these losses is considered a major solution to ensure global food security. Storage at low temperatures is an efficient practice to prolong postharvest performance of crops with minimal negative impact on produce quality or human health and the environment. However, many fresh produce commodities are susceptible to chilling temperatures, and the application of cold storage is limited as it would cause physiological chilling injury (CI) leading to reduced produce quality. Further, the primary CI becomes a preferred site for pathogens leading to decay and massive produce losses. Thus, chilling sensitive crops should be stored at higher minimal temperatures, which curtails their marketing life and in some cases necessitates the use of other storage strategies. Development of new knowledge about the biological basis for chilling tolerance in fruits and vegetables should allow development of both new varieties more tolerant to cold, and more efficient postharvest storage treatments and storage conditions. In order to improve the agricultural performance of modern crop varieties, including tomato, there is great potential in introgression of marker-defined genomic regions from wild species onto the background of elite breeding lines. To exploit this potential for improving tomato fruit chilling tolerance during postharvest storage, we have used in this research a recombinant inbred line (RIL) population derived from a cross between the red-fruited tomato wild species SolanumpimpinellifoliumL. accession LA2093 and an advanced Solanum lycopersicumL. tomato breeding line NCEBR-1, developed in the laboratory of the US co-PI. The original specific objectives were: 1) Screening of RIL population resulting from the cross NCEBR1 X LA2093 for fruit chilling response during postharvest storage and estimation of its heritability; 2) Perform a transcriptopmic and bioinformatics analysis for the two parental lines following exposure to chilling storage. During the course of the project, we learned that we could measure greater differences in chilling responses among specific RILs compared to that observed between the two parental lines, and thus we decided not to perform transcriptomic analysis and instead invest our efforts more on characterization of the RILs. Performing the transcriptomic analysis for several RILs, which significantly differ in their chilling tolerance/sensitivity, at a later stage could result with more significant insights. The RIL population, (172 lines), was used in field experiment in which fruits were examined for chilling sensitivity by determining CI severity. Following the field experiments, including 4 harvest days and CI measurements, two extreme tails of the response distribution, each consisting of 11 RILs exhibiting either high sensitivity or tolerance to chilling stress, were identified and were further examined for chilling response in greenhouse experiments. Across the RILs, we found significant (P < 0.01) correlation between field and greenhouse grown plants in fruit CI. Two groups of 5 RILs, whose fruits exhibited reproducible chilling tolerant/sensitive phenotypes in both field and greenhouse experiments, were selected for further analyses. Numerous genetic, physiological, biochemical and molecular variations were investigated in response to postharvest chilling stress in the selected RILs. We confirmed the differential response of the parental lines of the RIL population to chilling stress, and examined the extent of variation in the RIL population in response to chilling treatment. We determined parameters which would be useful for further characterization of chilling response in the RIL population. These included chlorophyll fluorescence Fv/Fm, water loss, total non-enzymatic potential of antioxidant activity, ascorbate and proline content, and expression of LeCBF1 gene, known to be associated with cold acclimation. These parameters could be used in continuation studies for the identification and genetic mapping of loci contributing to chilling tolerance in this population, and identifying genetic markers associated with chilling tolerance in tomato. Once genetic markers associated with chilling tolerance are identified, the trait could be transferred to different genetic background via marker-assisted selection (MAS) and breeding. The collaborative research established in this program has resulted in new information and insights in this area of research and the collaboration will be continued to obtain further insights into the genetic, molecular biology and physiology of postharvest chilling tolerance in tomato fruit. The US Co-PI, developed the RIL population that was used for screening and measurement of the relevant chilling stress responses and conducted statistical analyses of the data. Because we were not able to grow the RIL population under field conditions in two successive generations, we could not estimate heritability of response to chilling temperatures. However, we plan to continue the research, grow the RIL progeny in the field again, and determine heritability of chilling tolerance in a near future. The IS and US investigators interacted regularly and plan to continue and expand on this study, since combing the expertise of the Co-PI in genetics and breeding with that of the PI in postharvest physiology and molecular biology will have great impact on this line of research, given the significant findings of this one-year feasibility project.