Literature DB >> 28724072

Genome-Wide Analysis of Tar Spot Complex Resistance in Maize Using Genotyping-by-Sequencing SNPs and Whole-Genome Prediction.

Shiliang Cao, Alexander Loladze, Yibing Yuan, Yongsheng Wu, Ao Zhang, Jiafa Chen, Gordon Huestis, Jingsheng Cao, Vijay Chaikam, Michael Olsen, Boddupalli M Prasanna, Felix San Vicente, Xuecai Zhang.   

Abstract

Tar spot complex (TSC) is one of the most destructive foliar diseases of maize ( L.) in tropical and subtropical areas of Central and South America, causing significant grain yield losses when weather conditions are conducive. To dissect the genetic architecture of TSC resistance in maize, association mapping, in conjunction with linkage mapping, was conducted on an association-mapping panel and three biparental doubled-haploid (DH) populations using genotyping-by-sequencing (GBS) single-nucleotide polymorphisms (SNPs). Association mapping revealed four quantitative trait loci (QTL) on chromosome 2, 3, 7, and 8. All the QTL, except for the one on chromosome 3, were further validated by linkage mapping in different genetic backgrounds. Additional QTL were identified by linkage mapping alone. A major QTL located on bin 8.03 was consistently detected with the largest phenotypic explained variation: 13% in association-mapping analysis and 13.18 to 43.31% in linkage-mapping analysis. These results indicated that TSC resistance in maize was controlled by a major QTL located on bin 8.03 and several minor QTL with smaller effects on other chromosomes. Genomic prediction results showed moderate-to-high prediction accuracies in different populations using various training population sizes and marker densities. Prediction accuracy of TSC resistance was >0.50 when half of the population was included into the training set and 500 to 1,000 SNPs were used for prediction. Information obtained from this study can be used for developing functional molecular markers for marker-assisted selection (MAS) and for implementing genomic selection (GS) to improve TSC resistance in tropical maize.
Copyright © 2017 Crop Science Society of America.

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Year:  2017        PMID: 28724072     DOI: 10.3835/plantgenome2016.10.0099

Source DB:  PubMed          Journal:  Plant Genome        ISSN: 1940-3372            Impact factor:   4.089


  18 in total

1.  Population-tailored mock genome enables genomic studies in species without a reference genome.

Authors:  Felipe Sabadin; Humberto Fanelli Carvalho; Giovanni Galli; Roberto Fritsche-Neto
Journal:  Mol Genet Genomics       Date:  2021-11-09       Impact factor: 3.291

2.  Identification of Genes Related to Cold Tolerance and a Functional Allele That Confers Cold Tolerance.

Authors:  Ning Xiao; Yong Gao; Huangjun Qian; Qiang Gao; Yunyu Wu; Dongping Zhang; Xiaoxiang Zhang; Ling Yu; Yuhong Li; Cunhong Pan; Guangqing Liu; Changhai Zhou; Min Jiang; Niansheng Huang; Zhengyuan Dai; Chengzhi Liang; Zhou Chen; Jianmin Chen; Aihong Li
Journal:  Plant Physiol       Date:  2018-05-15       Impact factor: 8.340

3.  Effect of Trait Heritability, Training Population Size and Marker Density on Genomic Prediction Accuracy Estimation in 22 bi-parental Tropical Maize Populations.

Authors:  Ao Zhang; Hongwu Wang; Yoseph Beyene; Kassa Semagn; Yubo Liu; Shiliang Cao; Zhenhai Cui; Yanye Ruan; Juan Burgueño; Felix San Vicente; Michael Olsen; Boddupalli M Prasanna; José Crossa; Haiqiu Yu; Xuecai Zhang
Journal:  Front Plant Sci       Date:  2017-11-08       Impact factor: 5.753

4.  Estimation of physiological genomic estimated breeding values (PGEBV) combining full hyperspectral and marker data across environments for grain yield under combined heat and drought stress in tropical maize (Zea mays L.).

Authors:  Samuel Trachsel; Thanda Dhliwayo; Lorena Gonzalez Perez; Jose Alberto Mendoza Lugo; Mathias Trachsel
Journal:  PLoS One       Date:  2019-03-20       Impact factor: 3.752

5.  Genetic architecture of maize chlorotic mottle virus and maize lethal necrosis through GWAS, linkage analysis and genomic prediction in tropical maize germplasm.

Authors:  Chelang'at Sitonik; L M Suresh; Yoseph Beyene; Michael S Olsen; Dan Makumbi; Kiplagat Oliver; Biswanath Das; Jumbo M Bright; Stephen Mugo; Jose Crossa; Amsal Tarekegne; Boddupalli M Prasanna; Manje Gowda
Journal:  Theor Appl Genet       Date:  2019-05-16       Impact factor: 5.699

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

Authors:  Christine Nyaga; Manje Gowda; Yoseph Beyene; Wilson T Muriithi; Dan Makumbi; Michael S Olsen; L M Suresh; Jumbo M Bright; Biswanath Das; Boddupalli M Prasanna
Journal:  Genes (Basel)       Date:  2019-12-23       Impact factor: 4.096

7.  Introgression of Maize Lethal Necrosis Resistance Quantitative Trait Loci Into Susceptible Maize Populations and Validation of the Resistance Under Field Conditions in Naivasha, Kenya.

Authors:  Luka A O Awata; Beatrice E Ifie; Eric Danquah; MacDonald Bright Jumbo; L Mahabaleswara Suresh; Manje Gowda; Philip W Marchelo-Dragga; Michael Scott Olsen; Oluwaseyi Shorinola; Nasser Kouadio Yao; Prasanna M Boddupalli; Pangirayi B Tongoona
Journal:  Front Plant Sci       Date:  2021-05-03       Impact factor: 5.753

8.  Genetic Dissection of Quantitative Resistance to Common Rust (Puccinia sorghi) in Tropical Maize (Zea mays L.) by Combined Genome-Wide Association Study, Linkage Mapping, and Genomic Prediction.

Authors:  Jiaojiao Ren; Zhimin Li; Penghao Wu; Ao Zhang; Yubo Liu; Guanghui Hu; Shiliang Cao; Jingtao Qu; Thanda Dhliwayo; Hongjian Zheng; Michael Olsen; Boddupalli M Prasanna; Felix San Vicente; Xuecai Zhang
Journal:  Front Plant Sci       Date:  2021-07-02       Impact factor: 5.753

9.  Genomic Selection Outperforms Marker Assisted Selection for Grain Yield and Physiological Traits in a Maize Doubled Haploid Population Across Water Treatments.

Authors:  Diego Cerrudo; Shiliang Cao; Yibing Yuan; Carlos Martinez; Edgar Antonio Suarez; Raman Babu; Xuecai Zhang; Samuel Trachsel
Journal:  Front Plant Sci       Date:  2018-03-20       Impact factor: 5.753

Review 10.  Genomics-Enabled Next-Generation Breeding Approaches for Developing System-Specific Drought Tolerant Hybrids in Maize.

Authors:  Thirunavukkarsau Nepolean; Jyoti Kaul; Ganapati Mukri; Shikha Mittal
Journal:  Front Plant Sci       Date:  2018-04-11       Impact factor: 5.753

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