Rice Genomics and Genetics 2025, Vol.16, No.3, 159-179 http://cropscipublisher.com/index.php/rgg 166 4.3 Distribution and hotspots of SVs across rice subspecies Structural variation in the rice genome isn’t random. Studies of rice pan-genomes show that certain regions-especially those rich in transposable elements (TEs) or segmental duplications-tend to gather more structural changes (Lu et al., 2021). One common example is the pericentromeric area, where repetitive DNA is dense and insertions or deletions are more frequent. When researchers scan the genome using sliding windows, they often find that regions with more TEs also contain more novel insertions. This suggests TEs may be actively driving variation (Li et al., 2021). For instance, if a TE inserts itself into one rice variety but not another, that insertion appears as unique to that line. Over time, these insertions cluster in TE-rich zones, forming SV hotspots. Additionally, different rice subspecies show lineage-specific SV patterns. Certain large structural variants have become fixed in indica but are absent in japonica, and vice versa. For instance, an extensive deletion overlapping the flowering regulatory gene DTH8 is present only in indica populations, whereas a copy-number variant at the grain length gene GL7 is found only in japonica. These variants mark subspecies differentiation and often map to QTLs underlying phenotypic differences (such as grain shape or flowering time) between indica and japonica. Some regions of the genome, such as those harboring clusters of NBS-LRR disease resistance genes, are particularly prone to presence/absence variation and show dramatic structural divergence among subpopulations. By contrast, other regions-often those with housekeeping genes-remain structurally conserved. Using pan-genome data, researchers have even constructed “inversion indexes” to identify large inversions distinguishing subpopulations. In one study, 1 769 non-redundant inversions (≥100 bp) were catalogued across Asian rice, collectively spanning ~29% of the reference genome sequence. These inversions and other SV hotspots provide clues to rice evolutionary history and may underlie some adaptation traits unique to specific lineages. 4.4 Relationship between SVs and genetic diversity Structural variants (SVs) have a big impact on the genetic makeup and diversity of rice. Compared to single nucleotide polymorphisms (SNPs), SVs can remove or insert entire genes, revealing variations that SNPs might miss (Zhao et al., 2018). I find it especially intriguing how certain gene sequences show up in one group of rice but not in another, helping researchers tell subpopulations apart. For example, pan-genome studies show that some SVs are unique to groups like aus or aromatic rice, making them reliable indicators of those genetic lineages. When comparing wild and cultivated rice, more than 13 800 presence/absence variants have been identified that help distinguish between indica andjaponica types. These differences highlight their separate domestication paths, including the genetic bottlenecks they each experienced. Japonica rice seems to have gone through a narrower bottleneck, which means it holds fewer rare variants compared to indica. SVs also drive diversity by introducing new functions. Some rice types have genes that others don’t-often due to gene duplication or gene flow (Li et al., 2021). These extra genes may help plants resist disease or adapt to tough growing conditions. SVs can even affect nearby regions. Large inversions, for instance, can reduce recombination, which causes more genetic differences to build up between populations. In short, SVs aren’t just background noise in the genome. They often hold clues to traits we care about and help explain how rice varieties have developed over time. That’s why newer studies tend to analyze SVs alongside SNPs to better understand rice evolution and diversity. 5 Functional Implications of SVs in Rice 5.1 Structural variations and agronomic traits (e.g., yield, stress tolerance, flowering time) Structural variations in the rice genome can have major effects on agronomic traits by altering gene function or regulation. One clear example is a tandem duplication at the GL7 locus in some japonica rice, which was shown to increase grain length and improve grain appearance; this ~17-kb duplication (absent in indica) boosts the expression of a positive regulator of grain length, resulting in longer grains. Another classic case involves the Sub1Agene for submergence tolerance: tolerant rice varieties (e.g., the landrace FR13A) have an extra copy of the Sub1Atranscription factor gene (through duplication) that is not present in most intolerant varieties-this structural variation confers the ability to withstand prolonged flooding. Similarly, large insertions or deletions in promoter or
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