Association Mapping of Thousand Grain Weight using SSR and SNP Markers in Rice (Oryza sativa L.) Across Six Environments

Xiangong Chen,Haiqing Yin,Yufeng Yang,Jianjun Sun,Xiaojing Dang,Erbao Liu,Guohong Yang,Ya Wang,Delin Hong

doi:10.1007/s12042-021-09282-7

Xiangong Chen, Haiqing Yin + Show 7 more

Open Access

https://doi.org/10.1007/s12042-021-09282-7

Copy DOI

Abstract

Thousand grain weight (TGW) is an important determinant of rice yield, and correlates with grain size, plumpness and grain number per panicle. In rice, there are fewer association mapping studies relating grain weight traits using both SSR and SNP markers. In this study, in order to find robust SSR markers associated with TGW trait and mine elite accessions in rice, we investigated the TGW trait across six environments using a natural population consisted of 462 accessions, and then performed association mapping using both SSR and SNP markers. Using the six datasets from the six environments and their best linear unbiased estimator, we identified eight TGW associated SSR markers, with three environmentally stable and one newly found, on five chromosomes. The associated markers have genetic effect from 3.44% to 20.84%, and two of them carry stable elite allele with positive effect across different environments. Candidate interval association mapping using re-sequencing derived SNP/InDel markers further confirms the TGW-SSR association, and also suggests that 3 TGW-SSR associations were high confident in intervals of size from 176 to 603 kb. These results not only shed more lights on the genetics of TGW trait, but also suggest that the multi-allelic SSR markers should be used as an alternative power tool in gene or QTL mapping.

Highlights

Current food production is becoming limited because of shortages of cropland, water, and shortages of fertilizers that depend on fossil energy (Pimentel 2012)
Of the 462 accessions used in this study, part was from Vietnam, and part was from northeastern China and Japan, (Table S1)
We observed little genetic admixture among the accessions (Fig. 1), and this situation agrees well with previous studies (Liu et al 2015; Dang et al 2016; Edzesi et al 2016; Liu et al 2017). This result may partly because that a fewer marker used in inferring the population structure, and some admixture may be missed out

Summary

Introduction

Current food production is becoming limited because of shortages of cropland, water, and shortages of fertilizers that depend on fossil energy (Pimentel 2012). Today, used as the main food for more than half of the world’s population, rice is expected to give higher yield to meet the needs of the increasing population (Fageria 2007). State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing 210095, China. Cereal Crop Research Institute, Henan Academy of Agricultural Sciences, Zhenzhou 450002, China. Crop yield is a quantitative trait and has complex genetic background. The panicle number, grain number, and grain weight are three main components of the yield. Beyond the panicle number per unit area and grain number per panicle, the improvement of grain weight is the major way to further increase the yield (Xing and Zhang 2010)

Methods

Results

Conclusion