AIMC Topic: Genome, Plant

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Next-generation translational genomics for developing future crops.

Functional & integrative genomics
Advancements in translational genomics have revolutionized crop breeding, driving us from traditional breeding methods towards next-generation strategies that integrate genomic, transcriptomic, and phenotypic data to expedite crop improvement. There ...

Deciphering the sequence basis and application of transcriptional initiation regulation in plant genomes through deep learning.

Genome biology
BACKGROUND: Transcription initiation is a key checkpoint in plant gene regulation, yet the DNA features that determine where and the frequency of the genes start transcription remain unclear.

Revolution and advances in gene editing and genomics technology for developing climate-resilient legume crops: developments and prospects.

Plant molecular biology
Legumes are essential for agriculture and food security. Biotic and abiotic stresses pose significant challenges to legume production, lowering productivity levels. Most legumes must be genetically improved by introducing alleles that give pest and d...

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
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...

In silico prediction of variant effects: promises and limitations for precision plant breeding.

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik
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...

Distribution patterns of N6-methyladenine in the rye genome.

Scientific reports
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,...

Breeding perspectives on tackling trait genome-to-phenome (G2P) dimensionality using ensemble-based genomic prediction.

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik
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...

DeepRice6mA: A convolutional neural network approach for 6mA site prediction in the rice Genome.

PloS one
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...

Genome-wide annotation and comparative analysis of miniature inverted-repeat transposable elements (MITEs) in six pear species.

Planta
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...

Transcripts and genomic intervals associated with variation in metabolite abundance in maize leaves under field conditions.

BMC genomics
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 ...