Comparison of Phenotypic and Marker‐Assisted Selection for Quantitative Traits in Sweet Corn

Marker-assisted selection is proposed to be more effective than phenotypic selection in improving complex traits with low heritability. This study was designed to test empirically the efficiency of marker-assisted selection (MAS) vs. phenotypic selection (PS) in enhancing economically important characters in sweet corn using composite populations consisting of selected F2:3 families from two populations. In previous studies in our laboratory, these segregating populations were developed and assayed for genes influencing sweet corn emergence and eating quality. The 214 F2:3 families in the first population (W678su1 × IL731ase1) were classified into three sub-populations according to segregation for the se1gene. Marker-assisted selection and phenotypic selection were applied on the two homozygous sugary1 and sugary enhancer1 sub-populations separately. The second population consisted of 117 F2:3 families from the cross of Ia453sh2 × IL451bsh2. The genotypic selection was based on the polymorphism of five RFLP markers linked to QTL associated with significant effects on emergence and eating quality in the F2:3 generation. Twenty percent of the families in each population with the highest and lowest genotypic scores and phenotypic performance values were selected to constitute the MAS and PS composites, respectively. Emergence was evaluated in four different environments in Illinois and Wisconsin, while eating quality traits were evaluated in Illinois only. Results for emergence, with relatively high h2, in two out of three populations indicated that marker-assisted selection was superior to phenotypic selection. The effectiveness of MAS on enhancing stand establishment and eating quality will be discussed.

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Marker-assisted selection for quantitative traits

Cropp Breeding and Applied Biotechnology ◽

10.1590/s1984-70332011000500008 ◽

2011 ◽

Vol 11 (spe) ◽

pp. 50-55 ◽

Cited By ~ 11

Author(s):

Ivan Schuster

Keyword(s):

Molecular Markers ◽

Cost Reduction ◽

Marker Assisted Selection ◽

Quantitative Traits ◽

Large Scale ◽

Recurrent Selection ◽

Phenotypic Selection ◽

Breeding Programs ◽

The Subject ◽

Selection For

Although thousands of scientific articles have been published on the subject of marker-assisted selection (MAS) and quantitative trait loci (QTL), the application of MAS for QTL in plant breeding has been restricted. Among the main causes for this limited use are the low accuracy of QTL mapping and the high costs of genotyping thousands of plants with tens or hundreds of molecular markers in routine breeding programs. Recently, new large-scale genotyping technologies have resulted in a cost reduction. Nevertheless, the MAS for QTL has so far been limited to selection programs using several generations per year, where phenotypic selection cannot be performed in all generations, mainly in recurrent selection programs. Methods of MAS for QTL in breeding programs using self-pollination have been developed.

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Marker assisted selection for confirming F1 plants for tidal tolerant rice variety development

Amazonian Journal of Plant Research ◽

10.26545/ajpr.2020.b00075x ◽

2020 ◽

Vol 4 (3) ◽

pp. 668-678

Author(s):

Mithun Saha ◽

Md. Niuz Morshed Khan ◽

Sujan Kumar Kundu ◽

Md. Monirul Islam ◽

Sabina Yasmin ◽

...

Keyword(s):

Marker Assisted Selection ◽

Rice Variety ◽

Selection For

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Marker Assisted Selection for Common Bean Diseases Improvements in Tanzania: Prospects and Future Needs

Plant Breeding from Laboratories to Fields ◽

10.5772/52823 ◽

2013 ◽

Cited By ~ 3

Author(s):

George Muhamba ◽

Luseko Amos ◽

Deogracious Protas ◽

Paul Mbogo ◽

Susan Nchimbi-Msoll

Keyword(s):

Common Bean ◽

Marker Assisted Selection ◽

Future Needs ◽

Selection For

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Relatedness severely impacts accuracy of marker-assisted selection for disease resistance in hybrid wheat

Heredity ◽

10.1038/hdy.2013.139 ◽

2013 ◽

Vol 112 (5) ◽

pp. 552-561 ◽

Cited By ~ 40

Author(s):

M Gowda ◽

Y Zhao ◽

T Würschum ◽

C FH Longin ◽

T Miedaner ◽

...

Keyword(s):

Disease Resistance ◽

Marker Assisted Selection ◽

Hybrid Wheat ◽

Selection For

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Direct and Marker-Assisted Selection for Resistance to Common Bacterial Blight in Common Bean

Crop Science ◽

10.2135/cropsci2011.08.0445 ◽

2012 ◽

Vol 52 (4) ◽

pp. 1511-1521 ◽

Cited By ~ 10

Author(s):

Robert W. Duncan ◽

Robert L. Gilbertson ◽

Shree P. Singh

Keyword(s):

Common Bean ◽

Marker Assisted Selection ◽

Bacterial Blight ◽

Common Bacterial Blight ◽

Selection For

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Mendelian Genetics and Selection for Quantitative Traits in Poultry: Results and Perspectives

World s Poultry Science Journal ◽

10.1079/wps19700016 ◽

1970 ◽

Vol 26 (2) ◽

pp. 571-586 ◽

Cited By ~ 5

Author(s):

P. Merat

Keyword(s):

Quantitative Traits ◽

Mendelian Genetics ◽

Selection For

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Identification of Associations between SSR Markers and Quantitative Traits of Maize (Zea mays L.)

Agronomy ◽

10.3390/agronomy11010182 ◽

2021 ◽

Vol 11 (1) ◽

pp. 182

Author(s):

Jan Bocianowski ◽

Kamila Nowosad ◽

Barbara Wróbel ◽

Piotr Szulc

Keyword(s):

Zea Mays ◽

Ssr Markers ◽

Marker Assisted Selection ◽

Quantitative Traits ◽

Zea Mays L ◽

Fresh Weight ◽

Multiple Traits ◽

Good Tool ◽

Maize Varieties ◽

Hybrid Maize

Microsatellite or simple sequence repeat (SSR) markers have wide applicability for genetic analysis in crop plant improvement strategies. Marker-assisted selection is an important tool for plant breeders to increase the efficiency of a breeding process, especially for multigenic traits, highly influenced by the environment. In this paper, the relationships between SSR markers and 26 quantitative traits of hybrid maize varieties (Zea mays L.) were analyzed. Association analyses were performed based on 30 SSR primers in a set of thirteen hybrid maize varieties. A total of 112 SSR markers were detected in these genotypes. The number of alleles per locus ranged from 1 to 17, with the average number of alleles per locus equal to 3.7. The number of molecular markers associated with observed traits ranged from 1 (for the number of kernels in row, ears weight and fresh weight of one plant) to 14 (for damage of maize caused by P. nubilalis) in 2016 as well as from 1 (for soil plant analysis development—SPAD, the number of grains in ear and fresh weight of one plant) to 12 (for carotenoids content) in 2017. The sum of statistically significant associations between SSR markers and at least one trait was equal to one hundred sixty in 2016 as well as one hundred twenty-five in 2017. Marker trait associations (MTAs) were found on the basis of regression analysis. The proportion of the total phenotypic variances of individual traits explained by the marker ranged from 24.4% to 77.7% in the first year of study and from 24.3% to 77.9% in 2017. Twenty-two SSR markers performed a significant effect on at least one tested trait in both years of experiment. The three markers (phi021/4, phi036/3, and phi061/2) can be a good tool in marker-assisted selection because they allow simultaneous selection for multiple traits in both years of study, such as the number of kernels in row and the number of grains in ear (phi021/4), the number of plant after germination, the number of plants before harvest, and the number of ears (phi036/3), as well as moisture of grain and length of ears (phi061/2).

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