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PubMed2026

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↗

PubMed2026

The MexMAGIC population reveals the genetic architecture of traits exhibiting clinal variation in Mexican native maize.

Defining the genetic basis of local adaptation is a key goal of evolutionary biology and crop improvement. Theory predicts that when selective pressures follow differences in the environment, a cline will be established. Clines can be exploited to uncover adaptive variation by association of alleles with the environment. However, monotonic phenotypic change over a cline is not necessarily mirrored in the behavior of genetic variants and population structure can further complicate analysis. To study genetic and phenotypic variation across the environment, we developed a multi-parent advanced generation inter-cross (MAGIC) population using eight Mexican native maize (Zea mays L. ssp. mays) varieties sourced from distinct agroecological zones. We evaluated the population in a common garden in Mexico and mapped tassel branching and flowering time, two traits that exhibit clinal variation. Variation in tassel branching was dominated by a single QTL with allele effects aligning to a negative elevational cline. By contrast, allele effects associated with 11 identified flowering time QTL were not consistently correlated with any one source environmental factor. Our observations support the prediction that genotype-environment association will be strongest under simple genetic architecture, although, even then, analysis in native populations may be confounded by population structure.

MAGIC↗

PubMed2025

Uncovering the genetic basis of competitiveness and the potential for cooperation in plant groups.

Crop productivity was transformed by incorporating dwarfing genes that made plants smaller and less competitive (more cooperative). Beyond such major shifts in plant size, however, it is not clear how much variation in competitiveness remains and how to find its genetic basis. We performed plant density experiments, using 484 lines of the Arabidopsis thaliana multi-parent advanced generation inter-cross population, to compare methods for mapping the genetic basis of plant competitiveness. We first found that a major dwarfing gene, the erecta allele, caused reduced competitiveness and higher group productivity. Then, measuring competitiveness more generally, we found: (i) extensive variation in generic measures of competitiveness that extended beyond the effects of the erecta allele; (ii) a novel genomic region underlying variation in competitiveness; and (iii) that some measures of competitiveness were more useful than others. Our results show how modern genomic resources, including multi-parent populations, could uncover hidden genes for more cooperative crop plants.

Arabidopsis↗

PubMed2025

Genetic basis and role of exotic accessions in cultivated cotton fiber quality improvement.

Exotic Gossypium accessions still harbor QTL‑validated alleles that, combined with CRISPR pyramiding and genomic selection, can break the entrenched fiber length-strength trade‑off. Cotton's four independent domestications twice in diploids and twice in allotetraploids offer a natural experiment in fiber improvement. Synthesizing three decades of data, we chart how polyploidy, selection and modern breeding have repeatedly reshaped the Gossypium genome. More than 15,000 quantitative trait locus (QTL) and genome wide association mapping studies (GWAS) hits converge on a handful of chromosomal "hotspots"; new MAGIC, NAM, NIL and long-read resources now narrow these peaks to < 200 kb, resolving causal genes such as GhHOX3, GhZF14 and GhMYB7. Multi-omics evidence links auxin, ethylene, gibberellin, brassinosteroid and strigolactone signaling to HDZIP IV, MYB, bHLH/HLH and ERF networks that drive fiber initiation, extreme cell elongation and cellulose deposition. Population genomics shows that ~ 40% of favorable fiber alleles are fixed in elite Gossypium hirsutum, yet wild diploids and landraces still harbor variants that could break the length strength trade-off. We propose a three-step roadmap genomic selection, CRISPR gene pyramiding and accelerated introgression to expand cotton's genetic base and deliver fibers suited to sustainable textile demands.

Gossypium↗