Genetic Mapping and Diversity in Plants and Animals

The paper evaluates GWAS efficiency in different plant populations, finding that inbred lines panels offer the best QTL detection power and precision, especially for low and intermediate heritability traits.

This study compares one-stage and two-stage GWAS methods, finding that a weighted two-stage approach reduces bias and improves power, especially in unbalanced data.

Primers anchored in conserved repeat sequence amplify thousands of maize middle-repetitive loci at once, with markers called from the low-copy sequence between copies for under $5 per sample.

The paper analyzes chloroplast genome diversity in 1,800 wild and cultivated rice accessions, revealing distinct domestication histories for aus and aromatic rice groups.

This study identifies genes underlying flowering time adaptation in maize landraces by integrating genomic mapping and association analysis across multiple environments.

DMAP visualizes and optimizes the correlation between physical and genetic maps, reducing data redundancy and highlighting anomalies in contig orientation.

This study identifies independent temperate adaptations in maize flowering time across different populations using GWAS and machine learning.