Literature DB >> 36131140

Genome-wide association studies of grain yield and quality traits under optimum and low-nitrogen stress in tropical maize (Zea mays L.).

Noel Ndlovu1, Charles Spillane2, Peter C McKeown1, Jill E Cairns3, Biswanath Das4, Manje Gowda5.   

Abstract

KEY MESSAGE: Genome-wide association study (GWAS) demonstrated that multiple genomic regions influence grain quality traits under nitrogen-starved soils. Using genomic prediction, genetic gains can be improved through selection for grain quality traits. Soils in sub-Saharan Africa are nitrogen deficient due to low fertilizer use and inadequate soil fertility management practices. This has resulted in a significant yield gap for the major staple crop maize, which is undermining nutritional security and livelihood sustainability across the region. Dissecting the genetic basis of grain protein, starch and oil content under nitrogen-starved soils can increase our understanding of the governing genetic systems and improve the efficacy of future breeding schemes. An association mapping panel of 410 inbred lines and four bi-parental populations were evaluated in field trials in Kenya and South Africa under optimum and low nitrogen conditions and genotyped with 259,798 SNP markers. Genetic correlations demonstrated that these populations may be utilized to select higher performing lines under low nitrogen stress. Furthermore, genotypic, environmental and GxE variations in nitrogen-starved soils were found to be significant for oil content. Broad sense heritabilities ranged from moderate (0.18) to high (0.86). Under low nitrogen stress, GWAS identified 42 SNPs linked to grain quality traits. These significant SNPs were associated with 51 putative candidate genes. Linkage mapping identified multiple QTLs for the grain quality traits. Under low nitrogen conditions, average prediction accuracies across the studied genotypes were higher for oil content (0.78) and lower for grain yield (0.08). Our findings indicate that grain quality traits are polygenic and that using genomic selection in maize breeding can improve genetic gain. Furthermore, the identified genomic regions and SNP markers can be utilized for selection to improve maize grain quality traits.
© 2022. The Author(s).

Entities:  

Year:  2022        PMID: 36131140     DOI: 10.1007/s00122-022-04224-7

Source DB:  PubMed          Journal:  Theor Appl Genet        ISSN: 0040-5752            Impact factor:   5.574


  28 in total

1.  TASSEL: software for association mapping of complex traits in diverse samples.

Authors:  Peter J Bradbury; Zhiwu Zhang; Dallas E Kroon; Terry M Casstevens; Yogesh Ramdoss; Edward S Buckler
Journal:  Bioinformatics       Date:  2007-06-22       Impact factor: 6.937

2.  Applying association mapping and genomic selection to the dissection of key traits in elite European wheat.

Authors:  Alison R Bentley; Marco Scutari; Nicolas Gosman; Sebastien Faure; Felicity Bedford; Phil Howell; James Cockram; Gemma A Rose; Tobias Barber; Jose Irigoyen; Richard Horsnell; Claire Pumfrey; Emma Winnie; Johannes Schacht; Katia Beauchêne; Sebastien Praud; Andy Greenland; David Balding; Ian J Mackay
Journal:  Theor Appl Genet       Date:  2014-10-02       Impact factor: 5.699

Review 3.  Role of ATP-binding cassette transporters in maintaining plant homeostasis under abiotic and biotic stresses.

Authors:  Anil Dahuja; Ranjeet R Kumar; Akshay Sakhare; Archana Watts; Bhupinder Singh; Suneha Goswami; Archana Sachdev; Shelly Praveen
Journal:  Physiol Plant       Date:  2020-12-20       Impact factor: 4.500

4.  Genetic architecture of maize kernel composition in the nested association mapping and inbred association panels.

Authors:  Jason P Cook; Michael D McMullen; James B Holland; Feng Tian; Peter Bradbury; Jeffrey Ross-Ibarra; Edward S Buckler; Sherry A Flint-Garcia
Journal:  Plant Physiol       Date:  2011-12-01       Impact factor: 8.340

5.  Empirical Comparison of Tropical Maize Hybrids Selected Through Genomic and Phenotypic Selections.

Authors:  Yoseph Beyene; Manje Gowda; Michael Olsen; Kelly R Robbins; Paulino Pérez-Rodríguez; Gregorio Alvarado; Kate Dreher; Star Yanxin Gao; Stephen Mugo; Boddupalli M Prasanna; Jose Crossa
Journal:  Front Plant Sci       Date:  2019-11-22       Impact factor: 5.753

6.  Profiling household double and triple burden of malnutrition in sub-Saharan Africa: prevalence and influencing household factors.

Authors:  Aaron K Christian; Fidelia Aa Dake
Journal:  Public Health Nutr       Date:  2021-04-26       Impact factor: 4.022

7.  Altered metabolome and microbiome features provide clues in understanding irritable bowel syndrome and depression comorbidity.

Authors:  Lijuan Han; Ling Zhao; Yong Zhou; Chao Yang; Teng Xiong; Lin Lu; Yusheng Deng; Wen Luo; Yang Chen; Qinwei Qiu; Xiaoxiao Shang; Li Huang; Zongchao Mo; Shaogang Huang; Suiping Huang; Zhi Liu; Wei Yang; Lixiang Zhai; Ziwan Ning; Chengyuan Lin; Tao Huang; Chungwah Cheng; Linda L D Zhong; Shuaicheng Li; Zhaoxiang Bian; Xiaodong Fang
Journal:  ISME J       Date:  2021-11-08       Impact factor: 10.302

8.  Genetic diversity and inter-trait relationship of tropical extra-early maturing quality protein maize inbred lines under low soil nitrogen stress.

Authors:  Pearl Abu; Baffour Badu-Apraku; Beatrice E Ifie; Pangirayi Tongoona; Leander D Melomey; Samuel K Offei
Journal:  PLoS One       Date:  2021-06-11       Impact factor: 3.240

9.  Application of Genomic Selection at the Early Stage of Breeding Pipeline in Tropical Maize.

Authors:  Yoseph Beyene; Manje Gowda; Paulino Pérez-Rodríguez; Michael Olsen; Kelly R Robbins; Juan Burgueño; Boddupalli M Prasanna; Jose Crossa
Journal:  Front Plant Sci       Date:  2021-06-28       Impact factor: 5.753

10.  Genomic prediction in CIMMYT maize and wheat breeding programs.

Authors:  J Crossa; P Pérez; J Hickey; J Burgueño; L Ornella; J Cerón-Rojas; X Zhang; S Dreisigacker; R Babu; Y Li; D Bonnett; K Mathews
Journal:  Heredity (Edinb)       Date:  2013-04-10       Impact factor: 3.821

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