ReviewTAG. Theoretical and applied genetics. Theoretische und angewandte Genetik2020
Genome optimization for improvement of maize breeding.
Review in TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed.
- Molecular and Genetic Characterization of Newly Released CIMMYT Inbred Maize Lines.Plants (Basel, Switzerland) · 2025Article
- Decades' progress and prospects on maize functional genomics and molecular breeding.Science China. Life sciences · 2025Review
- Integrating multi-omics and machine learning for disease resistance prediction in legumes.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Review
- Comparative analysis of chloroplast genomes and phylogenetic relationships of different pitaya cultivars.BMC genomics · 2025Article
- Unveiling the heterosis pattern of modern maize breeding in Southwest China through population structure and genetic diversity analysis.BMC plant biology · 2025Article
- Multi-omics assists genomic prediction of maize yield with machine learning approaches.Molecular breeding : new strategies in plant improvement · 2024Article
- A dimensionality-reduction genomic prediction method without direct inverse of the genomic relationship matrix for large genomic data.Plant cell reports · 2023Article
- G2P Provides an Integrative Environment for Multi-model genomic selection analysis to improve genotype-to-phenotype prediction.Frontiers in plant science · 2023Article
- Deep learning-empowered crop breeding: intelligent, efficient and promising.Frontiers in plant science · 2023Article
- Unraveling the potential of phenomic selection within and among diverse breeding material of maize (Zea mays L.).G3 (Bethesda, Md.) · 2022Article
- Genomic Prediction of Complex Traits in an Allogamous Annual Crop: The Case of Maize Single-Cross Hybrids.Methods in molecular biology (Clifton, N.J.) · 2022Article
- LightGBM: accelerated genomically designed crop breeding through ensemble learning.Genome biology · 2021Article
- Scaling up high-throughput phenotyping for abiotic stress selection in the field.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2021Review
- The genetic mechanism of heterosis utilization in maize improvement.Genome biology · 2021Article
- CRISPR-Cas technology in corn: a new key to unlock genetic knowledge and create novel products.Molecular breeding : new strategies in plant improvement · 2021Article
- Crop genetics research in Asia: improving food security and nutrition.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2020Article
- Breeding, Genetics, and Genomics Approaches for Improving Fusarium Wilt Resistance in Major Grain Legumes.Frontiers in genetics · 2020Review
- Development of a Highly Efficient Multiplex Genome Editing System in Outcrossing Tetraploid Alfalfa (Frontiers in plant science · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
key messageWe propose a new model to improve maize breeding that incorporates doubled haploid production, genomic selection, and genome optimization. Breeding 4.0 has been considered the next era of plant breeding. It is clear that the Breeding 4.0 era for maize will feature the integration of multi-disciplinary technologies including genomics and phenomics, gene editing and synthetic biology, and Big Data and artificial intelligence. The breeding approach of passively selecting ideal genotypes from designated genetic pools must soon evolve to virtual design of optimized genomes by pyramiding superior alleles using computational simulation. An optimized genome expressing optimal phenotypes, which may never actually be created, can function as a blueprint for breeding programs to use minimal materials and hybridizations to achieve maximum genetic gain. We propose a new breeding pipeline, "genomic design breeding," that incorporates doubled haploid production, genomic selection, and genome optimization and is facilitated by different scales of trait predictions and decision-making models. Successful implementation of the proposed model will facilitate the evolution of maize breeding from "art" to "science" and eventually to "intelligence," in the Breeding 4.0 era.
Indexed as
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.