scholarly journals Using Crop Databases to Explore Phenotypes: From QTL to Candidate Genes

Plants ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 2494
Author(s):  
Anne V. Brown ◽  
David Grant ◽  
Rex T. Nelson
Keyword(s):  
Regulatory Networks ◽  
Seed Quality ◽  
Data Sets ◽  
Crop Varieties ◽  
Genetics And Genomics ◽  
Soybean Genetics ◽  
Basic Studies ◽  
Agronomically Important Traits ◽  
New Crop ◽  
Seed Quality Traits

Seeds, especially those of certain grasses and legumes, provide the majority of the protein and carbohydrates for much of the world’s population. Therefore, improvements in seed quality and yield are important drivers for the development of new crop varieties to feed a growing population. Quantitative Trait Loci (QTL) have been identified for many biologically interesting and agronomically important traits, including many seed quality traits. QTL can help explain the genetic architecture of the traits and can also be used to incorporate traits into new crop cultivars during breeding. Despite the important contributions that QTL have made to basic studies and plant breeding, knowing the exact gene(s) conditioning each QTL would greatly improve our ability to study the underlying genetics, biochemistry and regulatory networks. The data sets needed for identifying these genes are increasingly available and often housed in species- or clade-specific genetics and genomics databases. In this demonstration, we present a generalized walkthrough of how such databases can be used in these studies using SoyBase, the USDA soybean Genetics and Genomics Database, as an example.

Potential of the C Genome of Different Variants of Brassica oleracea for the Improvement of Agronomic and Seed Quality Traits of B. napus Canola

Crop Science ◽  
2019 ◽  
Vol 59 (6) ◽  
pp. 2608-2620 ◽  
Author(s):  
Azam Nikzad ◽  
Berisso Kebede ◽  
Jaime Pinzon ◽  
Jani Bhavikkumar ◽  
Rong-Cai Yang ◽  
...  
Keyword(s):  
Brassica Oleracea ◽  
Seed Quality ◽  
Quality Traits ◽  
C Genome ◽  
Seed Quality Traits

scholarly journals Overcoming barriers to the registration of new plant varieties under the DUS system

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Chin Jian Yang ◽  
Joanne Russell ◽  
Luke Ramsay ◽  
William Thomas ◽  
Wayne Powell ◽  
...  
Keyword(s):  
Current System ◽  
Registration System ◽  
Crop Varieties ◽  
Property System ◽  
Dus Testing ◽  
History Of ◽  
New Varieties ◽  
Entire History ◽  
Combinatorial Space ◽  
New Crop

AbstractDistinctness, Uniformity and Stability (DUS) is an intellectual property system introduced in 1961 by the International Union for the Protection of New Varieties of Plants (UPOV) for safeguarding the investment and rewarding innovation in developing new plant varieties. Despite the rapid advancement in our understanding of crop biology over the past 60 years, the DUS system has changed little and is still largely dependent upon a set of morphological traits for testing candidate varieties. As the demand for more plant varieties increases, the barriers to registration of new varieties become more acute and thus require urgent review to the system. To highlight the challenges and remedies in the current system, we evaluated a comprehensive panel of 805 UK barley varieties that span the entire history of DUS testing. Our findings reveal the system deficiencies such as inconsistencies in DUS traits across environments, limitations in DUS trait combinatorial space, and inadequacies in currently available DUS markers. We advocate the concept of genomic DUS and provide evidence for a shift towards a robust genomics-enabled registration system for new crop varieties.

scholarly journals BioNetLink - An Architecture for Working with Network Data

2014 ◽  
Vol 11 (2) ◽  
pp. 68-79
Author(s):  
Matthias Klapperstück ◽  
Falk Schreiber
Keyword(s):  
Experimental Data ◽  
Biological Networks ◽  
Regulatory Networks ◽  
Large Data ◽  
Biological Data ◽  
Network Data ◽  
Data Sets ◽  
Dynamic Views ◽  
Gene Regulatory ◽  
Multiple Network

Summary The visualization of biological data gained increasing importance in the last years. There is a large number of methods and software tools available that visualize biological data including the combination of measured experimental data and biological networks. With growing size of networks their handling and exploration becomes a challenging task for the user. In addition, scientists also have an interest in not just investigating a single kind of network, but on the combination of different types of networks, such as metabolic, gene regulatory and protein interaction networks. Therefore, fast access, abstract and dynamic views, and intuitive exploratory methods should be provided to search and extract information from the networks. This paper will introduce a conceptual framework for handling and combining multiple network sources that enables abstract viewing and exploration of large data sets including additional experimental data. It will introduce a three-tier structure that links network data to multiple network views, discuss a proof of concept implementation, and shows a specific visualization method for combining metabolic and gene regulatory networks in an example.

scholarly journals Profiling Bioactivity of the ToxCast Chemical Library Using BioMAP Primary Human Cell Systems

2009 ◽  
Vol 14 (9) ◽  
pp. 1054-1066 ◽  
Author(s):  
Keith A. Houck ◽  
David J. Dix ◽  
Richard S. Judson ◽  
Robert J. Kavlock ◽  
Jian Yang ◽  
...  
Keyword(s):  
Human Cell ◽  
Regulatory Networks ◽  
Cell Types ◽  
Environmental Chemicals ◽  
Data Sets ◽  
Chemical Library ◽  
Data Set ◽  
Cell Systems ◽  
Disease Biology ◽  
Nfκb Pathway

The complexity of human biology has made prediction of health effects as a consequence of exposure to environmental chemicals especially challenging. Complex cell systems, such as the Biologically Multiplexed Activity Profiling (BioMAP) primary, human, cell-based disease models, leverage cellular regulatory networks to detect and distinguish chemicals with a broad range of target mechanisms and biological processes relevant to human toxicity. Here the authors use the BioMAP human cell systems to characterize effects relevant to human tissue and inflammatory disease biology following exposure to the 320 environmental chemicals in the Environmental Protection Agency’s (EPA’s) ToxCast phase I library. The ToxCast chemicals were assayed at 4 concentrations in 8 BioMAP cell systems, with a total of 87 assay endpoints resulting in more than 100,000 data points. Within the context of the BioMAP database, ToxCast compounds could be classified based on their ability to cause overt cytotoxicity in primary human cell types or according to toxicity mechanism class derived from comparisons to activity profiles of BioMAP reference compounds. ToxCast chemicals with similarity to inducers of mitochondrial dysfunction, cAMP elevators, inhibitors of tubulin function, inducers of endoplasmic reticulum stress, or NFκB pathway inhibitors were identified based on this BioMAP analysis. This data set is being combined with additional ToxCast data sets for development of predictive toxicity models at the EPA. ( Journal of Biomolecular Screening 2009:1054-1066)

scholarly journals Machine Learning Speeding Up the Development of Portfolio of New Crop Varieties to Adapt to and Mitigate Climate Change

2021 ◽  
Author(s):  
Abdallah Bari ◽  
Hassan Ouabbou ◽  
abderrazek Jilal ◽  
Hamid Khazaei ◽  
Fred Stoddard ◽  
...  
Keyword(s):  
Climate Change ◽  
Machine Learning ◽  
Crop Varieties ◽  
Short Period ◽  
Speed Up ◽  
Increasing Demand ◽  
Mitigate Climate Change ◽  
High Yielding Varieties ◽  
New Crop ◽  
Adaptation And Mitigation

Climate change poses serious challenges to achieving food security in a time of a need to produce more food to keep up with the worlds increasing demand for food. There is an urgent need to speed up the development of new high yielding varieties with traits of adaptation and mitigation to climate change. Mathematical approaches, including ML approaches, have been used to search for such traits, leading to unprecedented results as some of the traits, including heat traits that have been long sought-for, have been found within a short period of time.

scholarly journals Using of Genome Editing Methods in Plant Breeding

2021 ◽  
Author(s):  
Venera S. Kamburova ◽  
Ilkhom B. Salakhutdinov ◽  
Shukhrat E. Shermatov ◽  
Ibrokhim Y. Abdurakhmonov
Keyword(s):  
Plant Breeding ◽  
Product Quality ◽  
Genome Editing ◽  
Abiotic Stresses ◽  
Main Task ◽  
Biotic And Abiotic Stresses ◽  
Crop Varieties ◽  
Crop Resistance ◽  
Time Required ◽  
New Crop

The main task of plant breeding is creating of high-yield, resistant to biotic and abiotic stresses crop varieties with high product quality. The using of traditional breeding methods is limited by the duration of the new crop varieties creation with the required agronomic traits. This depends not only on the duration of growing season and reaching of mature stage of plants (especially the long-period growth plants, e.g. trees), as well as is associated with applying of multiple stages of crossing, selection and testing in breeding process. In addition, conventional methods of chemical and physical mutagenesis do not allow targeting effect to genome. However, the introduction of modern DNA-technology methods, such as genome editing, has opened in a new era in plant breeding. These methods allow to carry out precise and efficient targeted genome modifications, significantly reducing the time required to get plants with desirable features to create new crop varieties in perspective. This review provides the knowledge about application of genome editing methods to increase crop yields and product quality, as well as crop resistance to biotic and abiotic stresses. In addition, future prospects for integrating these technologies into crop breeding strategies are also discussed.

Seed Germination and Seedling Vigour Improvement by Halophytic Seed Treatment in Black gram (Vigna mungo L.)

2021 ◽  
Author(s):  
R. Vinothini ◽  
K. Raja ◽  
R. Jerlin ◽  
S. Maragatham
Keyword(s):  
Tamil Nadu ◽  
Leaf Extract ◽  
Seed Quality ◽  
Black Gram ◽  
Salt Glands ◽  
Seedling Vigour ◽  
Aerial Parts ◽  
Salt Bladders ◽  
Seed Quality Traits ◽  
Physiological Characters

Background: Chenopodium plant is halophytic in nature in which the plant absorbs salt from soil and secrets the salts in aerial parts particularly in leaves and also has lot of macro and micro nutrients. This salt secretion by salt glands helps to survive the plants in saline conditions. The morpho-physiological characters act as barrier against mechanical damages, insects, excessive light and loss of water. Therefore, an experiment was conducted to enhance the seed quality traits viz., germination, speed of germination and seedling vigour in black gram by treating with the salt glands of Chenopodium.Methods: The experiment was conducted in the Department of Seed Science and Technology, Tamil Nadu Agricultural University, Coimbatore during 2019 - 2020. The black gram variety VBN 8 seeds were treated with different concentrations of Chenopodium leaf extract and salt bladders. Then, the seeds were assessed for its quality traits.Result: The experimental results showed that seeds soaked in Chenopodium leaf extract along with salt bladders @ 1.0% or salt bladders alone @ 0.2% for 3 h at 1:0.3 (w/v) ratio have recorded highest germination (97% and 96%) and seedling vigour (2280 and 2102). Nevertheless, analytical results indicated that the Chenopodium leaf extract and its salt bladders contain more amount of minerals particularly phosphorous (0.50%, 0.15%), potassium (0.83%, 1.11%), nitrogen (2.52%, 2.21%), calcium (16.00 ppm, 22.40 ppm), magnesium (190.56 ppm, 193.40 ppm), sodium (4.14 mg 100 g-1, 6.57 mg 100 g-1), chloride (0.14 mol. L-1, 0.17 mol. L-1), respectively, which favored the enhancement of seed qualities in black gram.

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