Genome-Wide Analyses and Prediction of Resistance to MLN in Large Tropical Maize Germplasm

被引:31
|
作者
Nyaga, Christine [1 ,2 ]
Gowda, Manje [2 ]
Beyene, Yoseph [2 ]
Muriithi, Wilson T. [1 ]
Makumbi, Dan [2 ]
Olsen, Michael S. [2 ]
Suresh, L. M. [2 ]
Bright, Jumbo M. [2 ]
Das, Biswanath [2 ]
Prasanna, Boddupalli M. [2 ]
机构
[1] Kenyatta Univ, Dept Agr Sci & Technol, Nairobi 4384400100, Kenya
[2] World Agroforestry Ctr ICRAF, Int Maize & Wheat Improvement Ctr CIMMYT, United Nat Ave, Nairobi 104100621, Kenya
关键词
GWAS; GP; validation; markers; resistance; maize lethal necrosis; CHLOROTIC-MOTTLE-VIRUS; LETHAL NECROSIS; ASSOCIATION; SELECTION; GENES; DIVERSITY;
D O I
10.3390/genes11010016
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
Maize lethal necrosis (MLN), caused by co-infection of maize chlorotic mottle virus and sugarcane mosaic virus, can lead up to 100% yield loss. Identification and validation of genomic regions can facilitate marker assisted breeding for resistance to MLN. Our objectives were to identify marker-trait associations using genome wide association study and assess the potential of genomic prediction for MLN resistance in a large panel of diverse maize lines. A set of 1400 diverse maize tropical inbred lines were evaluated for their response to MLN under artificial inoculation by measuring disease severity or incidence and area under disease progress curve (AUDPC). All lines were genotyped with genotyping by sequencing (GBS) SNPs. The phenotypic variation was significant for all traits and the heritability estimates were moderate to high. GWAS revealed 32 significantly associated SNPs for MLN resistance (at p < 1.0 x 10(-6)). For disease severity, these significantly associated SNPs individually explained 3-5% of the total phenotypic variance, whereas for AUDPC they explained 3-12% of the total proportion of phenotypic variance. Most of significant SNPs were consistent with the previous studies and assists to validate and fine map the big quantitative trait locus (QTL) regions into few markers' specific regions. A set of putative candidate genes associated with the significant markers were identified and their functions revealed to be directly or indirectly involved in plant defense responses. Genomic prediction revealed reasonable prediction accuracies. The prediction accuracies significantly increased with increasing marker densities and training population size. These results support that MLN is a complex trait controlled by few major and many minor effect genes.
引用
收藏
页数:16
相关论文
共 50 条
  • [1] Genome-wide association and genomic prediction of resistance to maize lethal necrosis disease in tropical maize germplasm
    Manje Gowda
    Biswanath Das
    Dan Makumbi
    Raman Babu
    Kassa Semagn
    George Mahuku
    Michael S. Olsen
    Jumbo M. Bright
    Yoseph Beyene
    Boddupalli M. Prasanna
    Theoretical and Applied Genetics, 2015, 128 : 1957 - 1968
  • [2] Genome-wide association and genomic prediction of resistance to maize lethal necrosis disease in tropical maize germplasm
    Gowda, Manje
    Das, Biswanath
    Makumbi, Dan
    Babu, Raman
    Semagn, Kassa
    Mahuku, George
    Olsen, Michael S.
    Bright, Jumbo M.
    Beyene, Yoseph
    Prasanna, Boddupalli M.
    THEORETICAL AND APPLIED GENETICS, 2015, 128 (10) : 1957 - 1968
  • [3] Genome-wide association study and genomic prediction of Fusarium ear rot resistance in tropical maize germplasm
    Liu, Yubo
    Hu, Guanghui
    Zhang, Ao
    Loladze, Alexander
    Hu, Yingxiong
    Wang, Hui
    Qu, Jingtao
    Zhang, Xuecai
    Olsen, Michael
    San Vicente, Felix
    Crossa, Jose
    Lin, Feng
    Prasanna, Boddupalli M.
    CROP JOURNAL, 2021, 9 (02): : 325 - 341
  • [4] Genome-wide association study and genomic prediction of Fusarium ear rot resistance in tropical maize germplasm
    Yubo Liu
    Guanghui Hu
    Ao Zhang
    Alexander Loladze
    Yingxiong Hu
    Hui Wang
    Jingtao Qu
    Xuecai Zhang
    Michael Olsen
    Felix San Vicente
    Jose Crossa
    Feng Lin
    Boddupalli M.Prasanna
    The Crop Journal, 2021, 9 (02) : 325 - 341
  • [5] Genetic Dissection of Resistance to Gray Leaf Spot by Combining Genome-Wide Association, Linkage Mapping, and Genomic Prediction in Tropical Maize Germplasm
    Kibe, Maguta
    Nair, Sudha K.
    Das, Biswanath
    Bright, Jumbo M.
    Makumbi, Dan
    Kinyua, Johnson
    Suresh, L. M.
    Beyene, Yoseph
    Olsen, Michael S.
    Prasanna, Boddupalli M.
    Gowda, Manje
    FRONTIERS IN PLANT SCIENCE, 2020, 11
  • [6] Genome-Wide Association Study and Prediction of Tassel Weight of Tropical Maize Germplasm in Multi-Parent Population
    Liu, Meichen
    Zhang, Yudong
    Shaw, Ranjan K.
    Zhang, Xingjie
    Li, Jinfeng
    Li, Linzhuo
    Li, Shaoxiong
    Adnan, Muhammad
    Jiang, Fuyan
    Bi, Yaqi
    Yin, Xingfu
    Fan, Xingming
    INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES, 2024, 25 (03)
  • [7] Genetic dissection of Striga hermonthica (Del.) Benth. resistance via genome-wide association and genomic prediction in tropical maize germplasm
    Gowda, Manje
    Makumbi, Dan
    Das, Biswanath
    Nyaga, Christine
    Kosgei, Titus
    Crossa, Jose
    Beyene, Yoseph
    Montesinos-Lopez, Osval A.
    Olsen, Michael S.
    Prasanna, Boddupalli M.
    THEORETICAL AND APPLIED GENETICS, 2021, 134 (03) : 941 - 958
  • [8] Genetic dissection of Striga hermonthica (Del.) Benth. resistance via genome-wide association and genomic prediction in tropical maize germplasm
    Manje Gowda
    Dan Makumbi
    Biswanath Das
    Christine Nyaga
    Titus Kosgei
    Jose Crossa
    Yoseph Beyene
    Osval A. Montesinos-López
    Michael S. Olsen
    Boddupalli M. Prasanna
    Theoretical and Applied Genetics, 2021, 134 : 941 - 958
  • [9] Genome-Wide Association Studies for Striga asiatica Resistance in Tropical Maize
    Pfunye, Arthur
    Rwafa, Rwafa
    Mabasa, Stanford
    Gasura, Edmore
    INTERNATIONAL JOURNAL OF GENOMICS, 2021, 2021
  • [10] Genome-Wide Analysis and Prediction of Resistance to Goss's Wilt in Maize
    Cooper, Julian S.
    Rice, Brian R.
    Shenstone, Esperanza M.
    Lipka, Alexander E.
    Jamann, Tiffany M.
    PLANT GENOME, 2019, 12 (02):