Biology subjects

Isidro y Sanchez, J.

Publications and source records attributed to Isidro y Sanchez, J..

3 recordsLinked to original sources

bioRxiv2025

Expanding the gain-variance Pareto via optimal recycling and genomic mating

The optimization of mating plans, or optimal genomic mating (OGM), is a powerful breeding strategy that balances genetic gain with the preservation of diversity, securing long-term improvement. However, existing OGM implementations neglect the recycling stage, where naive truncation selection dissipates the diversity initially safeguarded. Here, we propose an integrated strategy that couples optimal recycling with genomic mating to better control genetic diversity while delivering competitive genetic gains. Using stochastic simulations of line and hybrid breeding schemes, we show that the integrated strategy retained 1.6-2.0 times more diversity than OGM alone and 3.5-5.0 times more than truncation mating based on family means and the usefulness criterion (UC). These were equivalent to maintaining around 1.7 and 2.4 times less realized inbreeding rates. Additionally, it improved the efficiency of translating variance into gain by 21.6-49.8% and 67.4-108.2% compared to the sole implementation of OGM and truncation mating strategies. We also demonstrate the utility of our newly developed intuitive and standardized metric, proportion of additive standard deviation lost (PropSD), for managing diversity in the crossing and recycling stages. Pareto optimal solutions were achieved at around 2-3% and 4-5% PropSD without and with optimal recycling. Finally, we derive a closed-form expression quantifying the expected advantage of UC over mean-based mating. Modeling within-family variance offered limited additional benefit, mainly due to high family mean-to-standard-deviation variance ratios. Overall, our proposed framework advances genomic selection programs to be sustainable by effectively preserving genetic diversity for future genetic improvement.

genetics↗

bioRxiv2025

MateR: a novel framework for computing the usefulness criterion and applying genomic mating

Genomic mating uses genome-wide information to design crosses that maximize genetic gain while managing diversity. Expected gain is often predicted through the usefulness criterion, which depends on family means and variances. However, existing equations mix incompatible parametrizations when considering dominance effects. Furthermore, diversity control is often tuned with metrics that lack a direct link to loss of additive variation and long-term gain. We derived equations that compute family mean and within-family variance consistently under breeding and genotypic parametrizations by computing locus-specific values using genotypic frequencies and propagating them to the entire genome through linkage disequilibrium covariances. We also developed a diversity metric that estimates the proportion of additive standard deviation lost and integrated both advances into the MateR software. We evaluated performance in simulated diploid and autotetraploid crop populations across multiple breeding schemes and against existing tools. The new equations predicted family means and variances with near-perfect accuracy when true QTL effects were known. With estimated marker effects, correlations were roughly 0.55-0.90 for family mean and about 0.25 for within-family standard deviation. The diversity metric matched the expected loss of additive standard deviation under random sampling and tracked loss of genic variance under selection. This framework unifies prediction of cross usefulness under dominance and supplies an interpretable diversity control directly tied to long-term gain. Implemented in MateR, it applies to diploids and autopolyploids and accommodates common breeding program constraints, including hybrid schemes and testers.

genetics↗

bioRxiv2024

A pangenome and pantranscriptome of hexaploid oat

Oat grain is a traditional human food rich in dietary fiber that contributes to improved human health. Interest in the crop has surged in recent years owing to its use as the basis for plant-based milk analogs. Oat is an allohexaploid with a large, repeat-rich genome that was shaped by subgenome exchanges over evolutionary timescales. In contrast to many other cereal species, genomic research in oat is still at an early stage, and surveys of structural genome diversity and gene expression variability are scarce. Here, we present annotated chromosome-scale sequence assemblies of 33 wild and domesticated oats along with an atlas of gene expression across six tissues of different developmental stages in 23 accessions. We describe the interplay of gene expression diversity across subgenomes, accessions and tissues. Gene loss in the hexaploid is accompanied by compensatory up-regulation of the remaining homeologs, but this process is constrained by subgenome divergence. Chromosomal rearrangements have significantly impacted recent oat breeding. A large pericentric inversion associated with early flowering explains distorted segregation on chromosome 7D and a homeologous sequence exchange between chromosomes 2A and 2C in a semidwarf mutant has risen to prominence in Australian elite varieties. The oat pangeome will promote the adoption of genomic approaches to understanding the evolution and adaptation of domesticated oats and will accelerate their improvement.

genomics↗