Sequence-based deep learning predicts genetic variant effects at base-pair resolution, enabling precision breeding in crops and overcoming evolutionary constraints.
Genetic Mapping and Diversity in Plants and Animals
Moving in bioRxiv, Journal of Experimental Botany, Plant Physiology and Biochemistry, Plant, Cell & Environment, medRxiv, Nature Reviews Genetics, eLife, Genome Biology.
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Latest in Genetic Mapping and Diversity in Plants and Animals
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Multiallelic genotypic selection can be modeled and estimated from time-series data, revealing complex fitness interactions such as heterozygote advantage in populations.
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Rice WRKY transcription factors exhibit over 100 members with diverse structures and functions, creating significant challenges for precise functional characterization.
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Explainable AI models identified key genes and interactions predicting flowering time and biomass in switchgrass across diverse environments, revealing both known and novel regulators.
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Genetic variants in Arabidopsis thaliana significantly influence repeat content divergence, with over 50 loci linked to genome-wide repeat abundance variation.
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COSIGT accurately genotypes complex loci from low-coverage sequencing, outperforming existing tools at 1-2X coverage and enabling population-scale analysis.
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Genomics and biotechnology advances have identified key genetic loci and mechanisms that enable wheat to tolerate heat stress, accelerating breeding for climate resilience.
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A sequence-based classifier accurately identifies phenotype-associated plant genes with 80% precision across multiple species.
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