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. 2024 May 19;15(5):645.
doi: 10.3390/genes15050645.

The Landscape of Presence/Absence Variations during the Improvement of Rice

Xia Zhou  1 , Chenggen Qiang  2 , Lei Chen  3 , Dongjin Qing  3 , Juan Huang  3 , Jilong Li  2 , Yinghua Pan  3
Affiliations

The Landscape of Presence/Absence Variations during the Improvement of Rice

Xia Zhou et al. Genes (Basel). .

Abstract

Rice is one of the most important staple crops in the world; therefore, the improvement of rice holds great significance for enhancing agricultural production and addressing food security challenges. Although there have been numerous studies on the role of single-nucleotide polymorphisms (SNPs) in rice improvement with the development of next-generation sequencing technologies, research on the role of presence/absence variations (PAVs) in the improvement of rice is limited. In particular, there is a scarcity of studies exploring the traits and genes that may be affected by PAVs in rice. Here, we extracted PAVs utilizing resequencing data from 148 improved rice varieties distributed in Asia. We detected a total of 33,220 PAVs and found that the number of variations decreased gradually as the length of the PAVs increased. The number of PAVs was the highest on chromosome 1. Furthermore, we identified a 6 Mb hotspot region on chromosome 11 containing 1091 PAVs in which there were 29 genes related to defense responses. By conducting a genome-wide association study (GWAS) using PAV variation data and phenotypic data for five traits (flowering time, plant height, flag leaf length, flag leaf width, and panicle number) across all materials, we identified 186 significantly associated PAVs involving 20 cloned genes. A haplotype analysis and expression analysis of candidate genes revealed that important genes might be affected by PAVs, such as the flowering time gene OsSFL1 and the flag leaf width gene NAL1. Our work investigated the pattern in PAVs and explored important PAV key functional genes associated with agronomic traits. Consequently, these results provide potential and exploitable genetic resources for rice breeding.

Keywords: genome-wide association study; presence/absence variations; rice improvement.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
The number of PAVs of different sizes.
Figure 2
Figure 2
Distribution pattern of PAVs. (a) Number of PAVs on different chromosomes. (b) Distribution of hotspot regions for PAVs on chromosomes. Red boxes (b) represent centromere region. (c) Percentage of PAVs overlapping with different genomic regions.
Figure 3
Figure 3
GWAS analysis for heading date. (a,b) Manhattan plot and quantile–quantile (QQ) plots of PAV and heading date association in 148 rice varieties. Red dots indicate a significant correlation with phenotype, and red dashed lines show threshold (a). (c) A 55 bp deletion occurred within OsSFL1, exhibiting two haplotypes. (d) Comparison of heading date in Hap1 and Hap2. Statistical significance was calculated using Student’s t-test; * p < 0.05.
Figure 4
Figure 4
GWAS analysis for flag leaf width. (a,b) Manhattan plot and quantile–quantile (QQ) plots of PAV and flag leaf width association in 148 rice varieties. Red dots indicate significant correlation with phenotype, and red dashed lines show threshold (a). (c) A 5918 bp deletion occurred within the NAL1, exhibiting two haplotypes. (d) Comparison of heading date in Hap1 and Hap2. The statistical significance was calculated by Student’s t-test. * p < 0.05.
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