The construction of a maize-teosinte introgression population and quantitative trait loci analysis of their 21 agronomic traits.
Plant Sci
; 348: 112226, 2024 Nov.
Article
in En
| MEDLINE
| ID: mdl-39153574
ABSTRACT
Teosinte is a progenitor species of maize (Zea mays ssp. mays) that retains a significant reservoir of genetic resources unaltered via the domestication process. To harness and explore the genetic reservoirs inherent in teosinte, we used the cultivated publicly inbred line H95 and wild species PI566673 (Zea mays ssp. mexicana) to develop a set of introgression lines (ILs), including 366 BC2F5 lines. Using these lines, 12481 high-quality polymorphic homozygous single nucleotide polymorphisms were converted into 2358 bin markers based on Genotyping by Target Sequencing technology. The homozygous introgression ratio in the ILs was approximately 12.1â¯% and the heterozygous introgression ratio was approximately 5.7â¯%. Based on the population phenotypic data across 21 important agronomic traits collected in Sanya and Beijing, 185 and 156 quantitative trait loci (QTLs) were detected in Sanya and Beijing, respectively, with 64 stable QTLs detected in both locations. We detected 12 QTL clusters spanning 10 chromosomes consisting of diverse QTLs related to yield traits such as grain size and weight. In addition, we identified useful materials in the ILs for further gene cloning of related variations. For example, some heterogeneous inbred families with superior genetic purity, shorter target heterozygotes, and some ILs exhibit clear morphological variation associated with plant growth, development, and domestication, manifesting traits such as white stalks, sharp seeds, and cob shattering. In conclusion, our results provide a robust foundation for delving into the genetic reservoirs of teosinte, presenting a wealth of genetic resources and offering insight into the genetic architecture underlying maize agronomic traits.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Zea mays
/
Quantitative Trait Loci
Language:
En
Journal:
Plant Sci
Year:
2024
Document type:
Article
Affiliation country:
China
Country of publication:
Ireland