Pan-genome inversion index reveals evolutionary insights into the subpopulation structure of Asian rice (Oryza sativa)

Abstract

Understanding and exploiting genetic diversity is a key factor for the productive and stable production of rice. Utilizing 16 high-quality genomes that represent the subpopulation structure of Asian rice (O. sativa), plus the genomes of two close relatives (O. rufipogon and O. punctata), we built a pan-genome inversion index of 1,054 non-redundant inversions that span an average of ~ 14% of the O. sativa cv. Nipponbare reference genome sequence. Using this index we estimated an inversion rate of 1,100 inversions per million years in Asian rice, which is 37 to 73 times higher than previously estimated for plants. Detailed analyses of these inversions showed evidence of their effects on gene regulation, recombination rate, linkage disequilibrium and agronomic trait performance. Our study uncovers the prevalence and scale of large inversions (≥ 100 bp) across the pan-genome of Asian rice, and hints at their largely unexplored role in functional biology and crop performance.

Unravelling inversions: Technological advances, challenges, and potential impact on crop breeding

“…For example, Chen et al (2013) estimated that about 15.7-32.1 inversions occur approximately once every million years based on 214 inversions between AA and BB Oryza species. Recently, Zhou et al (2023) estimated an inversion rate of 67.4 inversions per million years using 1769 inversions, which is two to four times higher than previous estimations. The observed differences may arise from the differential capacity to identify inversions of varying sizes between the two studies, likely attributable to the accessibility and quality of the genomes used.…”

“…Recently, several inversion studies have been conducted on crops and fruit plants, including rice (Qin et al, 2021;Stein et al, 2018;Wang et al, 2018Wang et al, , 2023Zhou et al, 2023), soybean (Liu et al, 2020), barley (Jayakodi et al, 2020;Zhang et al, 2023), wheat (Walkowiak et al, 2020), brassica (Boideau et al, 2022;Cai et al, 2021), cotton (Jin et al, 2023;Ma et al, 2021), tomato (Wang et al, 2020) and cucumber (Li et al, 2022) (Hu et al, 2023).…”

“…This strategy has been implemented in several research studies. For example, Zhou et al (2023) captured the genetic diversity of Asian rice by investigating 73 rice genomes, which included two wild rice accessions. They constructed an inversion index within a pangenome framework, containing 1769 non-redundant inversions.…”

“…The authors demonstrated that their inversion classifier surpassed previous read alignment-based inversion calling methods, such as Delly (Rausch et al, 2012) and Lumpy (Layer et al, 2014). Similarly, Zhou et al (2023) implemented a machine-learning workflow to genotype inversions across high-throughput sequencing data from the 3K-Rice Genome Project, providing insights into species formation from the perspective of inversion events throughout evolutionary history. One limitation of these methods is that there is limited empirical training data, because inversions are relatively rare and plant genome sequencing efforts remain limited in scale.…”

Pan-genome inversion index reveals evolutionary insights into the subpopulation structure of Asian rice

“…To discover large inversions (>100 bp), we first tested four different analysis workflows (https://gitlab.kaust.edu.sa/zhouy0e/svfor-o.sativa) 74 on two genomes, i.e., GJ-temp: IRGSP-1.0 and XIadm: MH63 (the genome of Minghui 63 accession).…”