Chinese Bulletin of Botany ›› 2021, Vol. 56 ›› Issue (3): 284-295.DOI: 10.11983/CBB20200

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Genetic Analysis of Four Stigma Traits with Genic Male Sterile Line in Rice (Oryza sativa)

Jianhua Jiang1, Xiaojing Dang1, Wenhao Yao2, Mengzhu Hu2, Yuting Wang2, Changmin Hu1, Ying Zhang1, Dezheng Wang1,*()   

  1. 1Rice Genetic Breeding Key Laboratory of Anhui Province, Institute of Rice Research, Anhui Academy of Agricultural Sciences, Hefei 230031, China
    2Anhui Science and Technology University, Fengyang 233100, China
  • Received:2020-12-09 Accepted:2021-03-01 Online:2021-05-01 Published:2021-04-30
  • Contact: Dezheng Wang
  • About author:First author contact:

    † These authors contributed equally to this paper


To provide genetic information suitable for improving stigma-related traits of genic male sterile lines in rice. We investigated four stigma-related traits of 7001S (japonica genic male sterile line, P1), Z913S (indica genic male sterile line, P2), F1 (P1×P2), F2 and F2:3. Coefficients of linear correlation among four stigma-related traits were calculated, and genetic patterns were analyzed using mixed major-gene plus polygene inheritance models. We found an extremely significant linear positive correlation among four stigma traits, and the correlation coefficients were between 0.274 and 0.897. Genetic analysis revealed that, style length (SYL) and percentage of exserted stigma (PES) were controlled by two major genes with additive-dominant effects and one major gene with additive-equal-negative-dominant effects plus polygenes in F2:3, respectively. Stigma length (STL), SYL (except F2:3), the sum of stigma and style length (TSSL), and PES (except F2:3) were controlled by two major genes plus polygenes in F2 and F2:3. The two major genes expressed additive-dominant-epistatic effects but expressed additive-dominant effects of SYL in the F2:3 populations. Four stigma traits were mainly governed by major genes in two generations.

Key words: rice, genic male sterile line, stigma trait, major gene plus polygene model, genetic analysis