ArticleNational science review2026
A fast method for breeding by design via G × E interactions detected in large-scale climatic, phenomic and genomic data.
Article in National science review, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
1 citing paper in PubMed.
- Crop breeding by design: integrating big data for future food security.National science review · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Although large-scale populations are used to detect genes for polygenic traits, few studies integrate genes and gene-by-environment interactions (GEIs) into breeding by design. Here, we present Fast3VmrMLM, which uses eight big-data techniques to analyze climatic, phenomic and genomic data together to detect GEIs, decipher plasticity and guide breeding. In multi-environment joint analysis (MEJA) of maize, rice and soybean datasets, a total of 396 known genes and 84 known GEIs validated Fast3VmrMLM. In a 12-environment maize dataset, six GEIs interacting with five meteorological factors and two MEJA-detected GEIs helped to explain flowering time plasticity. Thirteen known genes, eight known GEIs and seven plasticity genes advanced flowering by 1.10-6.61 days, whereas nine known genes, one known GEI and three plasticity genes increased yield by 0.51-3.56 Mg·ha
Indexed as
Identifiers
What OpenQuestion holds
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.