Uncovering key salt-tolerant regulators through a combined eQTL and GWAS analysis using the super pan-genome in rice.

For sessile plants, gene expression plays a pivotal role in responding to salinity stress by activating or suppressing specific genes. However, our knowledge of genetic variations governing gene expression in response to salt stress remains limited in natural germplasm. Through transcriptome analysis of the Global Mini-Core Rice Collection consisting of a panel of 202 accessions, we identified 22 345 and 27 610 expression quantitative trait loci associated with the expression of 7787 and 9361 eGenes under normal and salt-stress conditions, respectively, leveraging the super pan-genome map. Notably, combined with genome-wide association studies, we swiftly pinpointed the potential candidate gene STG5-a major salt-tolerant locus known as qSTS5. Intriguingly, STG5 is required for maintaining Na+/K+ homeostasis by directly regulating the transcription of multiple members of the OsHKT gene family. Our study sheds light on how genetic variants influence the dynamic changes in gene expression responding to salinity stress and provides a valuable resource for the mining of salt-tolerant genes in the future.

A centromere map based on super pan-genome highlights the structure and function of rice centromeres.

Rice (Oryza sativa) is a significant crop worldwide with a genome shaped by various evolutionary factors. Rice centromeres are crucial for chromosome segregation, and contain some unreported genes. Due to the diverse and complex centromere region, a comprehensive understanding of rice centromere structure and function at the population level is needed. We constructed a high-quality centromere map based on the rice super pan-genome consisting of a 251-accession panel comprising both cultivated and wild species of Asian and African rice. We showed that rice centromeres have diverse satellite repeat CentO, which vary across chromosomes and subpopulations, reflecting their distinct evolutionary patterns. We also revealed that long terminal repeats (LTRs), especially young Gypsy-type LTRs, are abundant in the peripheral CentO-enriched regions and drive rice centromere expansion and evolution. Furthermore, high-quality genome assembly and complete telomere-to-telomere (T2T) reference genome enable us to obtain more centromeric genome information despite mapping and cloning of centromere genes being challenging. We investigated the association between structural variations and gene expression in the rice centromere. A centromere gene, OsMAB, which positively regulates rice tiller number, was further confirmed by expression quantitative trait loci, haplotype analysis and clustered regularly interspaced palindromic repeats (CRISPR)/CRISPR-associated protein 9 methods. By revealing the new insights into the evolutionary patterns and biological roles of rice centromeres, our finding will facilitate future research on centromere biology and crop improvement.

A rice variation map derived from 10 548 rice accessions reveals the importance of rare variants.

Detailed knowledge of the genetic variations in diverse crop populations forms the basis for genetic crop improvement and gene functional studies. In the present study, we analyzed a large rice population with a total of 10 548 accessions to construct a rice super-population variation map (RSPVM), consisting of 54 378 986 single nucleotide polymorphisms, 11 119 947 insertion/deletion mutations and 184 736 presence/absence variations. Assessment of variation detection efficiency for different population sizes revealed a sharp increase of all types of variation as the population size increased and a gradual saturation of that after the population size reached 10 000. Variant frequency analysis indicated that ∼90% of the obtained variants were rare, and would therefore likely be difficult to detect in a relatively small population. Among the rare variants, only 2.7% were predicted to be deleterious. Population structure, genetic diversity and gene functional polymorphism of this large population were evaluated based on different subsets of RSPVM, demonstrating the great potential of RSPVM for use in downstream applications. Our study provides both a rich genetic basis for understanding natural rice variations and a powerful tool for exploiting great potential of rare variants in future rice research, including population genetics and functional genomics.