AIMC Topic: Genome, Plant

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Effects of using deep learning to predict the geographic origin of barley genebank accessions on genome-environment association studies.

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik Aug 12, 2025
Genome-environment association (GEA) is an approach for identifying adaptive loci by combining genetic variation with environmental parameters, offering potential for improving crop resilience. However, its application to genebank accessions is limit...
Geography Genome, Plant Gene-Environment Interaction Deep Learning Polymorphism, Single Nucleotide Hordeum
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In silico prediction of variant effects: promises and limitations for precision plant breeding.

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik Jul 28, 2025
Sequence-based AI models show great potential for prediction of variant effects at high resolution, but their practical value in plant breeding remains to be confirmed through rigorous validation studies. Plant breeding has traditionally relied on ph...
Machine Learning Phenotype Models, Genetic Computer Simulation Plants Genetic Variation Genomics Genome, Plant Plant Breeding
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Distribution patterns of N6-methyladenine in the rye genome.

Scientific reports Jul 18, 2025
N6-methyladenine (6 mA) has emerged as a potential epigenetic marker in eukaryotic genomes, yet its precise distribution patterns and biological functions in plant genomes are still not fully understood. In this study, we investigated the occurrence,...
Epigenesis, Genetic Genome, Plant High-Throughput Nucleotide Sequencing DNA Methylation Chromosomes, Plant Tandem Mass Spectrometry Adenine Secale
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Breeding perspectives on tackling trait genome-to-phenome (G2P) dimensionality using ensemble-based genomic prediction.

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik Jul 4, 2025
Trait Genome-to-Phenome (G2P) dimensionality and "breeding context" combine to influence the realised prediction skill of different whole genome prediction (WGP) methods. Theory and empirical evidence both suggest there is likely to be "No Free Lunch...
Algorithms Phenotype Genomics Artificial Intelligence Machine Learning Quantitative Trait Loci Plant Breeding Models, Genetic Crops, Agricultural Genome, Plant
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DeepRice6mA: A convolutional neural network approach for 6mA site prediction in the rice Genome.

PloS one Jun 18, 2025
As one of the most critical post-replication modifications, N6-methylation (6mA) at adenine residue plays an important role in a variety of biological functions. Existing computational methods for identifying 6mA sites across large genomic regions te...
Neural Networks, Computer Deep Learning Convolutional Neural Networks ROC Curve Computational Biology Adenine DNA Methylation Genome, Plant Oryza
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Genome-wide annotation and comparative analysis of miniature inverted-repeat transposable elements (MITEs) in six pear species.

Planta Jun 16, 2025
Through multi-faceted comparative analysis of MITEs across six pear genomes, we revealed their distribution patterns, functional impacts and their significant role as genomic origins for miRNAs, with copy number being the most critical factor for MIT...
Pyrus MicroRNAs Evolution, Molecular Molecular Sequence Annotation Inverted Repeat Sequences Genome, Plant DNA Transposable Elements Phylogeny
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Transcripts and genomic intervals associated with variation in metabolite abundance in maize leaves under field conditions.

BMC genomics May 1, 2025
Plants exhibit extensive environment-dependent intraspecific metabolic variation, which likely plays a role in determining variation in whole plant phenotypes. However, much of the work seeking to use natural variation to link genes and transcript's ...
Plant Leaves Zea mays Genome, Plant Gene Expression Regulation, Plant Phenotype Genome-Wide Association Study Quantitative Trait Loci Transcriptome Genomics Metabolome
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Breaking down data silos across companies to train genome-wide predictions: A feasibility study in wheat.

Plant biotechnology journal Apr 20, 2025
Big data, combined with artificial intelligence (AI) techniques, holds the potential to significantly enhance the accuracy of genome-wide predictions. Motivated by the success reported for wheat hybrids, we extended the scope to inbred lines by integ...
Polymorphism, Single Nucleotide Genotype Triticum Feasibility Studies Genome, Plant Plant Breeding Phenotype Genome-Wide Association Study Genomics Artificial Intelligence
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Biological Prior Knowledge-Embedded Deep Neural Network for Plant Genomic Prediction.

Genes Mar 31, 2025
Genomic prediction is a powerful approach that predicts phenotypic traits from genotypic information, enabling the acceleration of trait improvement in plant breeding. Traditional genomic prediction methods have primarily relied on linear mixed mode...
Genome-Wide Association Study Genomics Polymorphism, Single Nucleotide Phenotype Deep Learning Neural Networks, Computer Genotype Genome, Plant Plant Breeding
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Leveraging Automated Machine Learning for Environmental Data-Driven Genetic Analysis and Genomic Prediction in Maize Hybrids.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Mar 6, 2025
Genotype, environment, and genotype-by-environment (G×E) interactions play a critical role in shaping crop phenotypes. Here, a large-scale, multi-environment hybrid maize dataset is used to construct and validate an automated machine learning framewo...
Gene-Environment Interaction Zea mays Environment Genome, Plant Genomics Genotype Machine Learning Phenotype Genome-Wide Association Study
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