Published: Dec. 6, 2022
genômicos e a alta complexidade genômica
Frontiers in Plant Science, Journal Year: 2024, Volume and Issue: 15
Published: April 18, 2024
Marker-assisted selection (MAS) plays a crucial role in crop breeding improving the speed and precision of conventional programmes by quickly reliably identifying selecting plants with desired traits. However, efficacy MAS depends on several prerequisites, precise phenotyping being key aspect any plant programme. Recent advancements high-throughput remote phenotyping, facilitated unmanned aerial vehicles coupled to machine learning, offer non-destructive efficient alternative traditional, time-consuming, labour-intensive methods. Furthermore, relies knowledge marker-trait associations, commonly obtained through genome-wide association studies (GWAS), understand complex traits such as drought tolerance, including yield components phenology. GWAS has limitations that artificial intelligence (AI) been shown partially overcome. Additionally, AI its explainable variants, which ensure transparency interpretability, are increasingly used recognised problem-solving tools throughout process. Given these rapid technological advancements, this review provides an overview state-of-the-art methods processes underlying each MAS, from genotyping analyses integration along entire workflow. In context, we specifically address challenges importance winter wheat for greater tolerance stable yields, regional droughts during critical developmental stages pose threat production. Finally, explore transition scientific progress practical implementation discuss ways bridge gap between cutting-edge developments breeders, expediting MAS-based tolerance.
Language: Английский
Citations
6
Plants, Journal Year: 2022, Volume and Issue: 11(16), P. 2139 - 2139
Published: Aug. 17, 2022
Marker-assisted selection (MAS) has been widely used in the last few decades plant breeding programs for mapping and introgression of genes economically important traits, which enabled development a number superior cultivars different crops. In sugarcane, is most source sugar bioethanol, marker work was initiated long ago; however, marker-assisted sugarcane lagging, mainly due to its large complex genome, high levels polyploidy heterozygosity, varied chromosomes, use low/medium-density markers. Genomic (GS) proven technology animal recently incorporated programs. GS potential tool rapid genotypes accelerating cycle. However, full could be realized by an integrated approach combining high-throughput phenotyping, genotyping, machine learning, speed with genomic selection. For better understanding integration, we comprehensively discuss concept genetic gain through breeder’s equation, methodology, prediction models, current status challenges accuracy, GS, phenotyping (HTP), genotyping (HTG), followed prospective applications improvement.
Language: Английский
Citations
20
Iran Journal of Computer Science, Journal Year: 2025, Volume and Issue: unknown
Published: March 18, 2025
Language: Английский
Citations
0
Crop Science, Journal Year: 2024, Volume and Issue: 65(1)
Published: Aug. 20, 2024
Abstract Plant breeding plays a crucial role in the development of high‐performing crop varieties that meet demands society. Emerging techniques offer potential to improve precision and efficiency plant programs; however, their optimal implementation requires refinement existing programs or design new ones. Stochastic simulations are cost‐effective solution for testing optimizing strategies. The aim this paper is provide an introduction stochastic simulation with software AlphaSimR students, researchers, experienced breeders. We present overview how use introductory vignette as well complete scripts self‐pollinated, clonal, hybrid crops, including relevant techniques, such backcrossing, speed breeding, genomic selection, index others. Our objective foundation understanding utilizing software, enabling readers adapt provided own even develop completely programs. By incorporating into education practice, next generation breeders will have valuable tool quest sustainable nutritious food sources growing population.
Language: Английский
Citations
3
Frontiers in Plant Science, Journal Year: 2023, Volume and Issue: 14
Published: Aug. 2, 2023
The sugarcane ratooning ability (RA) is the most important target trait for breeders seeking to enhance profitability of production by reducing planting cost. Understanding genetics governing RA could help identifying molecular markers that be used genomics-assisted breeding (GAB). A replicated field trial was conducted three crop cycles (plant cane, first ratoon, and second ratoon) using 432 clones conducting genome-wide association genomic prediction five sugar yield component traits RA. economic index (EI), stalk population (SP), weight (SW), tonns cane per hectare (TCH), sucrose (TSH) were estimated from data. total six putative quantitative loci eight nonredundant single-nucleotide polymorphism (SNP) associated with all tested appear unique. Seven candidate genes colocated significant SNPs traits. accuracies those moderate ranged 0.21 0.36. However, models fitting fixed effects each respective did not give any advantages over standard without effects. As a result this study, more robust in future clone selection sugarcane, potentially helping resolve genetic control sugarcane.
Language: Английский
Citations
8
The Crop Journal, Journal Year: 2023, Volume and Issue: 11(6), P. 1805 - 1815
Published: July 21, 2023
Sugarcane mosaic virus (SCMV) is the main etiological agent of sugarcane disease, which affects and other grass crops. Despite extensive characterization quantitative trait loci controlling resistance to SCMV in maize, genetic basis this largely unexplored. Here, a genome-wide association study was performed machine learning coupled with feature selection used for genomic prediction diverse panel. Nine single-nucleotide polymorphisms (SNPs) explained up 29.9% observed phenotypic variance 73-SNP set predicted high accuracy, precision, recall, F1 scores (the harmonic mean precision recall). Both marker sets were validated additional genotypes, SNPs 23.6% variation maximum accuracy 69.1%. Synteny analyses suggested that gene responsible majority maize absent sugarcane, explaining why major source has not been identified crop. Finally, using RNA-Seq data, markers associated annotated, coexpression network constructed identify biological processes involved resistance. This allowed identification candidate genes confirmed involvement stress responses, photosynthesis, regulation transcription translation SCMV. These results provide practical marker-assisted breeding approach target future studies
Language: Английский
Citations
7
Agriculture, Journal Year: 2024, Volume and Issue: 14(2), P. 279 - 279
Published: Feb. 8, 2024
Molecular breeding has revolutionized the improvement of forage crops by offering precise tools to enhance yield, quality, and environmental resilience. This review provides a comprehensive overview current technologies, applications, future directions in field crop molecular breeding. Technological advancements field, including Quantitative Trait Loci (QTL) mapping, Genome-Wide Association Studies (GWASs), genomic selection (GS), genome-editing such as CRISPR-Cas9, have significantly advanced identification incorporation beneficial traits into species. These approaches dramatically shortened cycles increased efficiency developing cultivars with improved disease resistance, stress tolerance, nutritional profiles. The implementation these technologies led notable successes, demonstrated case studies on various crops, showcasing enhanced quality adaptability challenging conditions. Furthermore, integration high-throughput phenotyping bioinformatics streamlined management large-scale data, facilitating more decisions. Looking ahead, this explores potential emerging application artificial intelligence predictive breeding, along associated ethical regulatory considerations. While we stand gain benefit from innovations, must also confront challenges posed climate change imperative sustainable agricultural practices. concludes emphasizing transformative impact critical need for ongoing research collaboration fully realize its potential.
Language: Английский
Citations
1
The Horticulture Journal, Journal Year: 2024, Volume and Issue: 93(3), P. 273 - 281
Published: Jan. 1, 2024
Language: Английский
Citations
1
Ecological Genetics and Genomics, Journal Year: 2023, Volume and Issue: 28, P. 100185 - 100185
Published: July 7, 2023
Language: Английский
Citations
3
Scientific Reports, Journal Year: 2022, Volume and Issue: 12(1)
Published: Oct. 26, 2022
Abstract Rubber tree ( Hevea brasiliensis ) is the main feedstock for commercial rubber; however, its long vegetative cycle has hindered development of more productive varieties via breeding programs. With availability H. genomic data, several linkage maps with associated quantitative trait loci have been constructed and suggested as a tool marker-assisted selection. Nonetheless, novel strategies are still needed, selection (GS) may facilitate rubber programs aimed at reducing required cycles performance assessment. Even though such methodology already shown to be promising breeding, increased model predictive capabilities practical application needed. Here, we developed machine learning-based approach predicting stem circumference based on molecular markers. Through divide-and-conquer strategy, propose neural network prediction system two stages: (1) subpopulation (2) phenotype estimation. This yielded higher accuracies than traditional statistical models in single-environment scenario. By delivering large accuracy improvements, our represents powerful use GS strategies. Therefore, incorporation learning techniques into an opportunity build robust optimize
Language: Английский
Citations
5