Genetic Diversity and Association Mapping of Grain-Size Traits in Rice Landraces from the Honghe Hani Rice Terraces System in Yunnan Province

Abstract

The Honghe Hani Rice Terraces System (HHRTS) of Yunnan Province is an important agricultural and cultural heritage landscape. Until now, a large number of local rice landraces have been planted. Mining excellent genes contained in these landraces provides a reference for variety improvement and new variety breeding. In this study, 96 rice landraces collected from the Hani terraces were planted in Honghe Mengzi, Yunnan Province, in 2013, 2014, 2015, and 2021, and five major grain traits were measured and analyzed. The genomic variation of 96 rice landraces was scanned by 201 simple sequence repeat (SSR) markers. The genetic diversity, population structure, and genetic relationships of the natural population were analyzed. The mixed linear model (MLM) method of the TASSEL software was used to analyze the associations between markers and traits. A total of 936 alleles were amplified by 201 pairs of SSR primers. The average number of observed alleles (Na), the effective number of alleles (Ne), Shannon’s information index (I), heterozygosity (H), and the polymorphism information content (PIC) per marker were 4.66, 2.71, 1.08, 0.15, and 0.55, respectively. Ninety-six landraces were divided into two groups by population structure, clustering, and principal component analysis, and indica rice was the main group. The coefficients of variation of the five traits ranged from 6.80 to 15.24%, and their broad heritabilities were more than 70%. In addition, there were positive correlations among the same grain traits between different years. Through MLM analysis, 2, 36, 7, 7, and 4 SSR markers were significantly associated with grain length (GL), grain width (GW), grain thickness (GT), grain length–width ratio (LWR), and thousand-grain weight (TGW), respectively. The explanation rates of phenotypic variation were 16.31 (RM449, Chr. 1)—23.51% (RM316, Chr. 9), 10.84 (RM523, Chr. 3; RM161/RM305, Chr. 5)—43.01% (RM5496, Chr. 1), 11.98 (RM161/RM305, Chr. 5)—24.72% (RM275, Chr. 6), 12.68 (RM126, Chr. 8)—36.96% (RM5496, Chr. 1), and 17.65 (RM4499, Chr. 2)—26.32% (RM25, Chr. 8), respectively. The associated markers were distributed on 12 chromosomes of the genome.

Establishment of Functional PCR-Based Markers against Bacterial Leaf Blight Disease in Rice Landraces of Yunnan Province of China

“…Due to the strong association of bacterial resistance in rice, we selected xa5, Xa7, xa13 and Xa21 genes in this study. China is one of the leading countries in the world in terms of rice production and Yunnan Province is considered as the center of diversity for rice genetic diversity and home to large number of indigenous rice landraces [47]. The rice landraces originating from China have shaped the evolution of bacterial blight resistance in cultivated varieties through the transfer of single resistance genes or in combination.…”

Investigating Genetic Diversity and Population Structure in Rice Breeding from Association Mapping of 116 Accessions Using 64 Polymorphic SSR Markers

“…This step reduces type I and II errors resulting from uneven allele frequency distribution between subgroups, which may lead to false associations between molecular markers and the trait of interest [17]. Recent efforts have been made to define the population structure in various crops, including rice, using diverse germplasm lines, including the development of core collections from national and international collections [18][19][20][21][22][23]. Previous studies utilized SSR markers alone [19,[24][25][26][27] or in conjunction with SNP markers [28,29] for similar investigations.…”

Interpretation and Spatiotemporal Analysis of Terraces in the Yellow River Basin Based on Machine Learning

“…Particularly in arid areas, they can modify the terrain and improve soil conditions, making more efficient use of rainfall and protecting water and soil [1,2], optimizing land use [3,4], increasing crop yields, and promoting sustainability [5]. In addition, terraces also serve as a diverse habitat for organisms [6] and are a cultural and historical heritage [7,8]. Studying the spatiotemporal changes in terraced-field areas (TRAs) and the factors driving these changes allows us to gain a better understanding and manage water resources, reduce soil erosion, and protect water quality, thereby promoting the sustainable development of terraces [9].…”