ArticleGenome biology2022
Prediction of evolutionary constraint by genomic annotations improves functional prioritization of genomic variants in maize.
Article in Genome biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed, 30 citations in OpenAlex.
- Translating functional molecular knowledge into crop-breeding success.Nature reviews. Genetics · 2026Review
- Advances in genomics-driven genetic decoding and genomic design breeding in tomato.Horticulture research · 2026Article
- Prioritization of deleterious mutations informs genomic prediction and increases the rate of gain in common bean (Phaseolus vulgaris L.), a simulation study.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Article
- Graph-based pangenome reveals structural variation dynamics during cucumber breeding.Nature genetics · 2026Article
- Optimizing genomic predictions in maize using a diversity panel and a multiparental population.The plant genome · 2026Article
- Protein structure and selection pressure in plants: using mutation to understand the functional importance of protein structure.BMC genomics · 2026Article
- Predicted protein 3D structures provide essential insights into the genetic architecture underlying phenotypic diversity in maize.Genome research · 2026Article
- Role of multi-omics in aquaculture genetics and breeding: current status and future perspective.Science China. Life sciences · 2025Review
- In silico prediction of variant effects: promises and limitations for precision plant breeding.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Review
- Cross-species modeling of plant genomes at single-nucleotide resolution using a pretrained DNA language model.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Improvement in genomic prediction of maize with prior gene ontology information depends on traits and environmental conditions.The plant genome · 2025Article
- Review
- Unifying approaches from statistical genetics and phylogenetics for mapping phenotypes in structured populations.PLoS biology · 2024Article
- Cross-species modeling of plant genomes at single nucleotide resolution using a pre-trained DNA language model.bioRxiv : the preprint server for biology · 2024Article
- Unveiling Genetic Potential for Equine Meat Production: A Bioinformatics Approach.Animals : an open access journal from MDPI · 2024Article
- Field-based high-throughput phenotyping enhances phenomic and genomic predictions for grain yield and plant height across years in maize.G3 (Bethesda, Md.) · 2024Article
- The effect of marker types and density on genomic prediction and GWAS of key performance traits in tetraploid potato.Frontiers in plant science · 2024Article
- Unraveling Prevalence and Effects of Deleterious Mutations in Maize Elite Lines across Decades of Modern Breeding.Molecular biology and evolution · 2023Article
- Relating pathogenic loss-of-function mutations in humans to their evolutionary fitness costs.eLife · 2023Article
- If it ain't broke, don't fix it: evaluating the effect of increased recombination on response to selection for wheat breeding.G3 (Bethesda, Md.) · 2022Article
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Authors and funding
2 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCrop improvement through cross-population genomic prediction and genome editing requires identification of causal variants at high resolution, within fewer than hundreds of base pairs. Most genetic mapping studies have generally lacked such resolution. In contrast, evolutionary approaches can detect genetic effects at high resolution, but they are limited by shifting selection, missing data, and low depth of multiple-sequence alignments. Here we use genomic annotations to accurately predict nucleotide conservation across angiosperms, as a proxy for fitness effect of mutations.
resultsUsing only sequence analysis, we annotate nonsynonymous mutations in 25,824 maize gene models, with information from bioinformatics and deep learning. Our predictions are validated by experimental information: within-species conservation, chromatin accessibility, and gene expression. According to gene ontology and pathway enrichment analyses, predicted nucleotide conservation points to genes in central carbon metabolism. Importantly, it improves genomic prediction for fitness-related traits such as grain yield, in elite maize panels, by stringent prioritization of fewer than 1% of single-site variants.
conclusionsOur results suggest that predicting nucleotide conservation across angiosperms may effectively prioritize sites most likely to impact fitness-related traits in crops, without being limited by shifting selection, missing data, and low depth of multiple-sequence alignments. Our approach-Prediction of mutation Impact by Calibrated Nucleotide Conservation (PICNC)-could be useful to select polymorphisms for accurate genomic prediction, and candidate mutations for efficient base editing. The trained PICNC models and predicted nucleotide conservation at protein-coding SNPs in maize are publicly available in CyVerse ( https://doi.org/10.25739/hybz-2957 ).
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