PubMed · 42552613
Long-read low-pass sequencing enhances variant detection in a peanut MAGIC population.
Abstract
Accurate genotyping accelerates crop improvement, yet long-read sequencing remains underused in breeding due to cost. We present a scalable long-read low-pass (LRLP) sequencing framework for high-throughput variant discovery and trait mapping. Using PacBio HiFi reads in an allotetraploid peanut (Arachis hypogaea; AABB, 2n = 4x = 40) MAGIC population, we generated both LRLP and short-read low-pass (SRLP) data. At comparable depths, LRLP achieved substantially greater whole-genome and gene-space coverage than SRLP. Data were analyzed using both a single-reference genome and an 18-parent pangenome graph constructed with KhufuPan, a new tool for graph-based genotyping. Across analytical approaches, LRLP consistently identified more SNPs, indels (2-1,000 bp), and structural variants (>1 kb) than SRLP, improving genotype resolution and selection accuracy, particularly for large structural variants. By reducing cost barriers and increasing variant discovery in complex genomes, LRLP provides a practical path for deploying advanced genomics in under-resourced and orphan crops critical to global food security.
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Kendall Lee, Walid Korani, Sameer Pokhrel, Hallie Wright, Philip C Bentz, Peggy Ozias-Akins, Ye Chu, Alex Harkess, Justin Vaughn, Josh Clevenger. 2026-09-02. Long-read low-pass sequencing enhances variant detection in a peanut MAGIC population.. https://doi.org/10.1093/g3journal%2Fjkag196
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