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Identifying Mutations by High Resolution Melting in a TILLING Population of Rice

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QTL mapping with near-isogenic lines in maize.

S J Szalma¹, B M Hostert, J R Ledeaux

¹USDA-ARS Plant Science Research Unit and Department of Crop Science, North Carolina State University, Raleigh, NC 27695, USA.

TAG. Theoretical and Applied Genetics. Theoretische Und Angewandte Genetik

|February 20, 2007

Summary

Maize near-isogenic lines (NILs) were developed using marker-assisted selection to map quantitative trait loci (QTLs) for flowering time. These NILs significantly reduced background introgression, providing a valuable resource for maize genetics research.

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Area of Science:

Plant Genetics
Maize Breeding
Quantitative Genetics

Background:

Developing near-isogenic lines (NILs) is crucial for dissecting complex genetic traits in crops.
Marker-assisted selection (MAS) enhances the efficiency of NIL development by precisely tracking introgressed genomic regions.

Purpose of the Study:

To create a set of maize NILs with targeted introgressions from donor line Tx303 into the B73 background.
To utilize these NILs for mapping quantitative trait loci (QTLs) associated with flowering time in both inbred and hybrid maize.
To assess the efficiency of MAS in minimizing background introgression during NIL development.

Main Methods:

Generated 89 maize NILs through three generations of backcrossing with MAS.
Utilized restriction fragment length polymorphism (RFLP) and simple sequence repeat (SSR) markers to genotype NILs and estimate introgression sizes.
Conducted field evaluations of NILs and their testcross hybrids over two years to map QTLs for flowering time traits (days to anthesis, days to silking, anthesis-silk interval).

Main Results:

Tx303 introgressions averaged 60 cM, with 89% of the donor genome represented across NILs.
Achieved significantly lower background introgression (average 2.5%) compared to conventional methods (expected 9.4%).
Identified QTLs for flowering time in both inbred NILs and their hybrids, with distinct QTLs detected across different environments (including drought stress) and genetic backgrounds.

Conclusions:

The developed maize NILs are a valuable resource for genetic mapping and dissecting the genetic architecture of flowering time.
MAS is highly effective in producing high-quality NILs with minimal background introgression.
Flowering time in maize is genetically complex, influenced by environment and genetic background, necessitating diverse mapping populations for comprehensive analysis.