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Alex Harkess

Publications and source records attributed to Alex Harkess.

2 recordsLinked to original sources

Development of a low-coverage whole genome sequencing screen for apomixis using a diverse set of Malus germplasm.

In the past decade, plant biologists have made several major discoveries pertaining to the genetic basis of apomixis (clonal propagation by seed) that have shown promise in preserving high-value hybrid rice and sorghum genotypes. This progress was made possible by foundational gene discovery efforts in model species and natural apomicts, but pleiotropic obstacles still limit its broad agricultural adoption, especially in eudicots. Thus, it follows that investigations of novel apomicts should lead to the development of new molecular tools for plant breeding. The two most common ways to identify clonal seed production are flow-cytometry seed screens and genome sequencing to compare the DNA sequences of the maternal parent and progeny, traditionally using low-throughput markers. While flow-cytometry has been the dominant method for more than two decades, it provides indirect information on the genetics of a resulting embryo and can be ineffective in certain species. Here we developed a method using short-read whole-genome sequencing at moderately low coverage (averaging 3X and 6X) to screen diverse Malus genotypes maintained in a USDA germplasm collection for clonal seed production. In total, we sequenced 55 genotypes, 1,216 of their embryos, and identified 17 previously undescribed apomictic genotypes. Several more were detected with the flow cytometry seed screen, which helped resolve certain types of reproduction and sources of noise in low-coverage datasets. This low-pass screening-by-sequencing method is a relatively low-cost, rapid method for detecting apomictic genotypes in diverse plant germplasm and when used thoughtfully in conjunction with flow cytometry, provides a new way to visualize the genetic outcomes of sexual and asexual reproduction in plants.

Apomixis

Long-read low-pass sequencing enhances variant detection in a peanut MAGIC population.

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.

Arachis