scholarly journals The advantage of parallel selection of domestication genes to accelerate crop improvement

2018 ◽  
Vol 19 (1) ◽  
Author(s):  
Martha Rendón-Anaya ◽  
Alfredo Herrera-Estrella
Crop Science ◽  
1997 ◽  
Vol 37 (3) ◽  
pp. 691-697 ◽  
Author(s):  
Mark E. Sorrells ◽  
William A. Wilson

Genes ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1407
Author(s):  
Larisa N. Efremova ◽  
Svetlana R. Strelnikova ◽  
Guzel R. Gazizova ◽  
Elena A. Minkina ◽  
Roman A. Komakhin

Synthetic promoters are vital for genetic engineering-based strategies for crop improvement, but effective methodologies for their creation and systematic testing are lacking. We report here on the comparative analysis of the promoters pro-SmAMP1 and pro-SmAMP2 from Stellaria media ANTIMICROBIAL PEPTIDE1 (AMP1) and ANTIMICROBIAL PEPTIDE2 (AMP2). These promoters are more effective than the well-known Cauliflower mosaic virus 35S promoter. Although these promoters share about 94% identity, the pro-SmAMP1 promoter demonstrated stronger transient expression of a reporter gene in Agrobacterium infiltration of Nicotiana benthamiana leaves, while the pro-SmAMP2 promoter was more effective for the selection of transgenic tobacco (Nicotiana tabacum) cells when driving a selectable marker. Using the cap analysis of gene expression method, we detected no differences in the structure of the transcription start sites for either promoter in transgenic plants. For both promoters, we used fine-scale deletion analysis to identify 160 bp-long sequences that retain the unique properties of each promoter. With the use of chimeric promoters and directed mutagenesis, we demonstrated that the superiority of the pro-SmAMP1 promoter for Agrobacterium-mediated infiltration is caused by the proline-inducible ACTCAT cis-element strictly positioned relative to the TATA box in the core promoter. Surprisingly, the ACTCAT cis-element not only activated but also suppressed the efficiency of the pro-SmAMP1 promoter under proline stress. The absence of the ACTCAT cis-element and CAANNNNATC motif (negative regulator) in the pro-SmAMP2 promoter provided a more constitutive gene expression profile and better selection of transgenic cells on selective medium. We created a new synthetic promoter that enjoys high effectiveness both in transient expression and in selection of transgenic cells. Intact promoters with differing properties and high degrees of sequence identity may thus be used as a basis for the creation of new synthetic promoters for precise and coordinated gene expression.


2008 ◽  
Vol 329 (1-2) ◽  
pp. 138-150 ◽  
Author(s):  
Dirk Saerens ◽  
Benoît Stijlemans ◽  
Toya Nath Baral ◽  
Giang Thanh Nguyen Thi ◽  
Ulrich Wernery ◽  
...  

Author(s):  
K. Shruthi ◽  
R. Siddaraju ◽  
K. Naveena ◽  
T.M. Ramanappa ◽  
C. Gireesh ◽  
...  

Background: Identification of suitable factors that influence significantly to the response is crucial for the traits based breeding program to make a better decision about improvement in productivity. Multiple linear regression (MLR) is the benchmark method commonly using to identify suitable factors for crop improvement. It doesn’t work always due to stringent assumption (Multicollinearity, Linearity) behind the MLR model. Here we tried to develop an efficient model for the selection of major traits that contribute to seed yield in soybean by comparing different models.Methods: Field experiment was conducted using 98 soybean core population through augmented design.18 morphometric traits obtain from soybean core population were considered under the study as regressors.Multiple linear regression (MLR), Principle component Regression (PCR), Regression tree and Random Forest models were compared to select traits based on prediction accuracy.Result: All the models identified the number of pods per plant (NPP) has the most influencing variable to the soybean yield. However random forest has a much higher prediction power (RMSE=4.59, MAPE=0.18) compared to other models under study. The results of random forest revealed that the number of pods per plant, number of branches per plant and other associated characters like plant height at harvest as highly influencing traits for seed yield in soybean.Finally, tried to identify genotypesthat possess superiority about most influencing morphological characters on seed yield using cluster analysis.


2016 ◽  
Vol 67 (6) ◽  
pp. 605 ◽  
Author(s):  
Vasileios Greveniotis ◽  
Vasilia A. Fasoula

Innovative approaches and new efficiencies in plant breeding are required to accelerate the progress of genetic improvement through selection. One such approach is the application of prognostic breeding, which is an integrated crop-improvement methodology that enables selection of plants for high crop yield potential by evaluating its two components: plant yield potential and stability of performance. Plant yield and stability are assessed concurrently in each generation by utilising the plant prognostic equation. The genetic material used for this study was 2350 F2 plants (C0) of the commercial maize hybrid Costanza. The study presents the results of the application of prognostic breeding for 6 years in two contrasting environments (A and B), starting from C0 and ending in C5. It utilises ultra-high selection pressures (1.5% to 0.5%) to isolate superior lines with crop yield comparable to Costanza, and estimates the annual genetic gain accomplished through application of this selection strategy. Application of prognostic breeding led to the isolation of superior lines whose productivity was comparable to Costanza. The productivity gap between Costanza and the best selection was reduced from 87% (C0) to 0.5% (C5) in trial 1 (environment A), from 87% (C0) to 2% (C5) in trial 2 (environment B) and from 70% (C0) to 1% (C3) in trial 3 (environment B). Genetic gain was much higher (up to 50%) in the early cycles C0–C2 of prognostic breeding and smaller in cycles C3–C5. The best lines selected were evaluated in randomised complete block trials across both environments and 2 years. Across years, the top two lines in environments A and B averaged 87% and 91% of the Costanza yield, respectively, and they had higher prolificacy (greater number of ears per plant) than Costanza. Across all cycles, the average annual genetic gain ranged from 23% to 36% in the different trials, providing evidence that selection efficiency can be significantly maximised by using this breeding strategy.


Author(s):  
Tinee Adlak ◽  
Sushma Tiwari ◽  
M. K. Tripathi ◽  
Neha Gupta ◽  
Vinod Kumar Sahu ◽  
...  

Plant breeding is mainly concerned with genetic improvement of crops through hybridization, screening and selection of advance lines. The conventional methods give advance varieties with desirable traits but take consume more time (6 to 12 years) to achieve. Biotechnology tools makes breeding methods more advance by reducing the time to get improved varieties. Other than conventional methods varietal advancement can be achieved by applying plant tissue culture, transgenic approaches and molecular breeding methods. Crop improvement by using biotechnology approaches is mostly concerned with protoplast fusion to get somatic hybrids, gene transfer to get genetically modified organisms and use of DNA markers to select trait of interests. Variety with improved biotic and abiotic stress resistance can be developed in less time and more accuracy using recent biotechnological approaches. Several advance tools are being utilized for that purpose including, nanotechnology, bioinformatics tools offers new era of genomics assisted molecular breeding. Next Generation Sequencing and high throughput genotyping approaches are increasing efficiency and output of biotechnological tools in agriculture. Current review focused on overview of biotechnological tools being applied for crop improvement.


2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Sikander Singh Cheema ◽  
Amardeep Singh ◽  
Hassène Gritli

For the economic growth of the crop, the optimal utilization of soil is found to be an open area of research. An efficient utilization includes various advantages such as watershed insurance, expanded biodiversity, and reduction of provincial destitution. Generally, soils present synthetic confinements for crop improvement. Therefore, in this paper, a novel diversified crop model is proposed to predict the suitable soil for good production of the crop. The proposed model utilizes a quantum value-based gravitational search algorithm (GSA) to optimize the best solution. Various features of soil are required to be investigated before crop selection. These features are refined further by applying quantum optimization. The crop selection based upon the soil requirement does not require any additional fertilizers which will reduce the production cost. Thus, the proposed model can select the optimal crop according to the soil components using the gravitational search algorithm. Therefore, the gravitational search algorithm is applied to the quantum values obtained from the crop and soil dataset. Extensive experiments show that the proposed model achieves an optimal selection of crops.


HortScience ◽  
2015 ◽  
Vol 50 (6) ◽  
pp. 777-779 ◽  
Author(s):  
Kevin M. Folta

Vavilov’s Law of Homologous Series indicates that heritable variation for a given trait will occur in different species based on parallel selection. The conclusion comes from Vavilov’s study of extensive collections and careful attention to phenotypic variation across taxa. The same examination of variation can be applied to traits using the power of genetic and genomic resolution, because parallel traits would be expected to be governed by the same genetic loci, and perhaps even common mutations. In this review, these concepts are applied to two central traits—the control of “shattering” of kernels in cereals and in the control of photoperiodic flowering. One of the strengths of the law is that it can make predictions about traits and perhaps the genes or genomic regions that control them. With respect to genetic variation, the occurrence and physical location of genes associated with kernel retention may be predicted. Many grains share mutations, such as the Sh 1 gene, which were selected in parallel. Selection of the Sh1 gene led to higher yields due to better kernel retention. While the genes affected are often the same, the types of mutations are not, implying convergent selection. Flowering time is governed by multiple loci, so variation may be attributed only to a few candidates, yet because of the number of regulators the predictive power of the law is lower. The modern application of the Law of Homologous Series is that it allows basic researchers or plant breeders to make predictions about the genes controlling key traits, although the genetic basis of variation is likely not conserved.


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