Bulk pollen pollination in maize for efficient construction of introgression populations with high genome coverage

Wang, Pingxi; Zhang, Hongwei; Lyle, Demar; Li, Dongdong; Wang, Guoying; Pan, Qingchun; Wang, Jianhua

doi:10.1111/pbr.12684

Cited by 3 publications

(1 citation statement)

References 22 publications

(24 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We determined the number of recombination events following previously reported methods used for F 1 -DH populations [16,35]. First, the number of recombination events of each chromosome was calculated in each F 1 -DH line of the 23 DH populations (containing 2233 lines in total).…”

Section: Determination Of the Two Recombination Parametersmentioning

confidence: 99%

Recombination Pattern Characterization via Simulation Using Different Maize Populations

Ren

Gong

et al. 2020

IJMS

Self Cite

View full text Add to dashboard Cite

Efficient recombination is critical to both plant breeding and gene cloning. However, almost all traditional recombination studies and genetic improvements require the slow and labor-intensive population construction process, and little is known about the recombination characteristics of populations of different types, generations, and origins. Here, we provide a simple and efficient simulation method for population construction based on doubled haploid (DH) and intermated B73 × Mo17 maize (IBM) populations to predict the recombination pattern. We found that the chromosomes had 0, 1, 2, and 3 recombination events that occurred at rates of 0.16, 0.30, 0.23, and 0.15, respectively, in the DH and the recombination rate of each chromosome in the IBM population ranged from 0 to 12.1 cM per 125 kb. Based on the observed recombination parameters, we estimated the number of recombination events and constructed the linkage maps of the simulated DH and recombination inbred line (RIL) populations. These simulated populations exhibited similar recombination patterns compared with the real populations, suggesting the feasibility of this simulation approach. We then compared the recombination rates of the simulated populations of different types (DH induced or self-crossed), generations, and origins (using the 8, 16, and 32 multiparent advanced generation intercross (MAGIC) populations), and suggested a rapid and cost-effective population construction procedure for breeders and geneticists, while maintaining an optimal recombination rate. This study offers a convenient method for optimizing the population construction process and has broader implications for other crop species, thereby facilitating future population studies and genetic improvement strategies.

show abstract

Section: Determination Of the Two Recombination Parametersmentioning

confidence: 99%

Recombination Pattern Characterization via Simulation Using Different Maize Populations

Ren

Gong

et al. 2020

IJMS

Self Cite

View full text Add to dashboard Cite

show abstract

Cloning of a new allele of ZmAMP1 and evaluation of its breeding value in hybrid maize

Wang¹,

Yang²,

Li³

et al. 2023

The Crop Journal

View full text Add to dashboard Cite

Genomic Prediction across Structured Hybrid Populations and Environments in Maize

et al. 2021

Plants

View full text Add to dashboard Cite

Genomic prediction (GP) across different populations and environments should be enhanced to increase the efficiency of crop breeding. In this study, four populations were constructed and genotyped with DNA chips containing 55,000 SNPs. These populations were testcrossed to a common tester, generating four hybrid populations. Yields of the four hybrid populations were evaluated in three environments. We demonstrated by using real data that the prediction accuracies of GP across structured hybrid populations were lower than those of within-population GP. Including relatives of the validation population in the training population could increase the prediction accuracies of GP across structured hybrid populations drastically. G × E models (including main and genotype-by-environment effect) had better performance than single environment (within environment) and across environment (including only main effect) GP models in the structured hybrid population, especially in the environment where yields had higher heritability. GP by implementing G × E models in two cross-validation schemes indicated that, to increase the prediction accuracy of a new hybrid line, it would be better to field-test the hybrid line in at least one environment. Our results would be helpful for designing training population and planning field testing in hybrid breeding.

show abstract

Bulk pollen pollination in maize for efficient construction of introgression populations with high genome coverage

Cited by 3 publications

References 22 publications

Recombination Pattern Characterization via Simulation Using Different Maize Populations

Recombination Pattern Characterization via Simulation Using Different Maize Populations

Cloning of a new allele of ZmAMP1 and evaluation of its breeding value in hybrid maize

Genomic Prediction across Structured Hybrid Populations and Environments in Maize

Contact Info

Product

Resources

About