The Genetic Architecture of Maize (Zea mays L.) Kernel Weight Determination

被引:40
|
作者
Alvarez Prado, Santiago [1 ]
Lopez, Cesar G. [2 ]
Lynn Senior, M. [3 ]
Borras, Lucas [1 ]
机构
[1] Univ Nacl Rosario, Fac Ciencias Agr, Zavalla, Santa Fe, Argentina
[2] Univ Lomas Zamora, Fac Ciencias Agr, RA-1836 Lavallol, Buenos Aires, Argentina
[3] Syngenta Seeds Inc, Res Triangle Pk, NC 27709 USA
来源
G3-GENES GENOMES GENETICS | 2014年 / 4卷 / 09期
关键词
kernel weight; kernel growth rate; grain-filling duration; genetic background effects; complex traits; Multiparent Advanced Generation Inter-Cross (MAGIC); multiparental populations; MPP; QUANTITATIVE TRAIT LOCI; PARENTAL INBRED LINES; YIELD COMPONENTS; GRAIN-YIELD; PHYSIOLOGICAL MATURITY; STATISTICAL POWER; MOLECULAR MARKERS; DIGENIC EPISTASIS; COMPLEX TRAITS; QTL DETECTION;
D O I
10.1534/g3.114.013243
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
Individual kernel weight is an important trait for maize yield determination. We have identified genomic regions controlling this trait by using the B73xMo17 population; however, the effect of genetic background on control of this complex trait and its physiological components is not yet known. The objective of this study was to understand how genetic background affected our previous results. Two nested stable recombinant inbred line populations (N209xMo17 and R18xMo17) were designed for this purpose. A total of 408 recombinant inbred lines were genotyped and phenotyped at two environments for kernel weight and five other traits related to kernel growth and development. All traits showed very high and significant (P < 0.001) phenotypic variability and medium-to-high heritability (0.60-0.90). When N209xMo17 and R18xMo17 were analyzed separately, a total of 23 environmentally stable quantitative trait loci (QTL) and five epistatic interactions were detected for N209xMo17. For R18xMo17, 59 environmentally stable QTL and 17 epistatic interactions were detected. A joint analysis detected 14 stable QTL regardless of the genetic background. Between 57 and 83% of detected QTL were population specific, denoting medium-to-high genetic background effects. This percentage was dependent on the trait. A meta-analysis including our previous B73xMo17 results identified five relevant genomic regions deserving further characterization. In summary, our grain filling traits were dominated by small additive QTL with several epistatic and few environmental interactions and medium-to-high genetic background effects. This study demonstrates that the number of detected QTL and additive effects for different physiologically related grain filling traits need to be understood relative to the specific germplasm.
引用
收藏
页码:1611 / 1621
页数:11
相关论文
共 50 条
  • [1] Independent genetic control of maize (Zea mays L.) kernel weight determination and its phenotypic plasticity
    Alvarez Prado, Santiago
    Sadras, Victor O.
    Borras, Lucas
    JOURNAL OF EXPERIMENTAL BOTANY, 2014, 65 (15) : 4479 - 4487
  • [2] Genetic dissection of stage-dependent dry matter accumulation in maize (Zea mays L.) kernel
    Liu, Jian-ju
    Yu, Hui
    Xue, Ming
    Liu, Bao-shen
    Xu, Ming-liang
    Chen, Sai-hua
    EUPHYTICA, 2022, 218 (10)
  • [3] Unraveling the genetic architecture of subtropical maize (Zea mays L.) lines to assess their utility in breeding programs
    Thirunavukkarasu, Nepolean
    Hossain, Firoz
    Shiriga, Kaliyugam
    Mittal, Swati
    Arora, Kanika
    Rathore, Abhishek
    Mohan, Sweta
    Shah, Trushar
    Sharma, Rinku
    Namratha, Pottekatt Mohanlal
    Mithra, Amitha S. V.
    Mohapatra, Trilochan
    Gupta, Hari Shankar
    BMC GENOMICS, 2013, 14
  • [4] Genetic dissection of the maize (Zea mays L.) MAMP response
    Zhang, Xinye
    Valdes-Lopez, Oswaldo
    Arellano, Consuelo
    Stacey, Gary
    Balint-Kurti, Peter
    THEORETICAL AND APPLIED GENETICS, 2017, 130 (06) : 1155 - 1168
  • [5] Genetic Dissection of Internode Length Above the Uppermost Ear in Four RIL Populations of Maize (Zea mays L.)
    Ku, Lixia
    Cao, Liru
    Wei, Xiaomin
    Su, Huihui
    Tian, Zhiqiang
    Guo, Shulei
    Zhang, Liangkun
    Ren, Zhenzhen
    Wang, Xiaobo
    Zhu, Yuguang
    Li, Guohui
    Wang, Zhiyong
    Chen, Yanhui
    G3-GENES GENOMES GENETICS, 2015, 5 (02): : 281 - 289
  • [6] Genetic dissection of stage-dependent dry matter accumulation in maize (Zea mays L.) kernel
    Jian-ju Liu
    Hui Yu
    Ming Xue
    Bao-shen Liu
    Ming-liang Xu
    Sai-hua Chen
    Euphytica, 2022, 218
  • [7] Identification of quantitative trait loci for kernel-related traits and the heterosis for these traits in maize (Zea mays L.)
    Liu, Yinghong
    Yi, Qiang
    Hou, Xianbin
    Hu, Yufeng
    Li, Yangping
    Yu, Guowu
    Liu, Hanmei
    Zhang, Junjie
    Huang, Yubi
    MOLECULAR GENETICS AND GENOMICS, 2020, 295 (01) : 121 - 133
  • [8] Detection of QTLs controlling fast kernel dehydration in maize (Zea mays L.)
    Qian, Y. L.
    Zhang, X. Q.
    Wang, L. F.
    Chen, J.
    Chen, B. R.
    Lv, G. H.
    Wu, Z. C.
    Guo, J.
    Wang, J.
    Qi, Y. C.
    Li, T. C.
    Zhang, W.
    Ruan, L.
    Zuo, X. L.
    GENETICS AND MOLECULAR RESEARCH, 2016, 15 (03)
  • [9] Genetic variation of growth dynamics in maize (Zea mays L.) revealed through automated non-invasive phenotyping
    Muraya, Moses M.
    Chu, Jianting
    Zhao, Yusheng
    Junker, Astrid
    Klukas, Christian
    Reif, Jochen C.
    Altmann, Thomas
    PLANT JOURNAL, 2017, 89 (02) : 366 - 380
  • [10] Association Mapping for Enhancing Maize (Zea mays L.) Genetic Improvement
    Yan, Jianbing
    Warburton, Marilyn
    Crouch, Jonathan
    CROP SCIENCE, 2011, 51 (02) : 433 - 449