Dataset Information

Substitution Mapping of the Major Quantitative Trait Loci Controlling Stigma Exsertion Rate from Oryza glumaepatula.

ABSTRACT:

Background

Stigma exsertion rate (SER) is a key determinant for the outcrossing ability of male sterility lines (MSLs) in hybrid rice seed production. In the process of domestication, the outcrossing ability of cultivated rice varieties decreased, while that of wild Oryza species kept strong. Here, we detected the quantitative trait loci (QTLs) controlling SER using a set of single-segment substitution lines (SSSLs) derived from O. glumaepatula, a wild Oryza species.

Results

Seven QTLs for SER were located on 5 chromosomes. qSER-1a and qSER-1b were located on chromosome 1. qSER-3a and qSER-3b were mapped on chromosome 3, and qSER-3b was further located at an estimated interval of 898.8?kb by secondary substitution mapping. qSER-5, qSER-9 and qSER-10 were identified on chromosomes 5, 9 and 10, respectively, and qSER-9 was delimited to an estimated region of 551.9?kb by secondary substitution mapping. The additive effects of the 7 QTLs ranged from 10.6% to 14.8%, which were higher than those of most loci for SER reported previously.

Conclusions

qSER-1a and qSER-1b are novel loci for SER on chromosome 1. All of the 7 QTLs have major effects on SER. The major QTLs of SER will help to develop MSLs with strong outcrossing ability.

SUBMITTER: Tan Q

PROVIDER: S-EPMC7283377 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Publications

Substitution Mapping of the Major Quantitative Trait Loci Controlling Stigma Exsertion Rate from Oryza glumaepatula.

Tan Quanya Q Zou Tuo T Zheng Mingmin M Ni Yuerong Y Luan Xin X Li Xiaohui X Yang Weifeng W Yang Zifeng Z Zhu Haitao H Zeng Ruizhen R Liu Guifu G Wang Shaokui S Fu Xuelin X Zhang Guiquan G

Rice (New York, N.Y.) 20200609 1

<h4>Background</h4>Stigma exsertion rate (SER) is a key determinant for the outcrossing ability of male sterility lines (MSLs) in hybrid rice seed production. In the process of domestication, the outcrossing ability of cultivated rice varieties decreased, while that of wild Oryza species kept strong. Here, we detected the quantitative trait loci (QTLs) controlling SER using a set of single-segment substitution lines (SSSLs) derived from O. glumaepatula, a wild Oryza species.<h4>Results</h4>Seven ...[more]

PMID: 32519122

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Project description:A new mixed-model method was developed for mapping quantitative trait loci (QTL) by incorporating multiple polygenic covariance structures. First, we used genome-wide markers to calculate six different kinship matrices. We then partitioned the total genetic variance into six variance components, one corresponding to each kinship matrix, including the additive, dominance, additive × additive, dominance × dominance, additive × dominance, and dominance × additive variances. The six different kinship matrices along with the six estimated polygenic variances were used to control the genetic background of a QTL mapping model. Simulation studies showed that incorporating epistatic polygenic covariance structure can improve QTL mapping resolution. The method was applied to yield component traits of rice. We analyzed four traits (yield, tiller number, grain number, and grain weight) using 278 immortal F2 crosses (crosses between recombinant inbred lines) and 1619 markers. We found that the relative importance of each type of genetic variance varies across different traits. The total genetic variance of yield is contributed by additive × additive (18%), dominance × dominance (14%), additive × dominance (48%), and dominance × additive (15%) variances. Tiller number is contributed by additive (17%), additive × additive (22%), and dominance × additive (43%) variances. Grain number is mainly contributed by additive (42%), additive × additive (19%), and additive × dominance (31%) variances. Grain weight is almost exclusively contributed by the additive (73%) variance plus a small contribution from the additive × additive (10%) variance. Using the estimated genetic variance components to capture the polygenic covariance structure, we detected 39 effects for yield, 39 effects for tiller number, 24 for grain number, and 15 for grain weight. The new method can be directly applied to polygenic-effect-adjusted genome-wide association studies (GWAS) in human and other species.

Dataset Information

Substitution Mapping of the Major Quantitative Trait Loci Controlling Stigma Exsertion Rate from Oryza glumaepatula.

Background

Results

Conclusions

Publications

Substitution Mapping of the Major Quantitative Trait Loci Controlling Stigma Exsertion Rate from Oryza glumaepatula.

Similar Datasets

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