Identification and verification of low-tillering QTL based on a new model of genetic analysis in wheat.

Effective tiller number (ETN) directly affects panicle number and is closely related to wheat grain yield. Mining quantitative trait loci (QTLs) associated with wheat tiller number and analyzing the correlation between tiller number and other important agronomic traits can provide the theoretical basis for molecular breeding. In this study, we first proposed and established a novel genetic analysis framework of "multiple environmental assessments-depth analysis of individual traits-comprehensive evaluation of various traits-friendly marker development-verification in different backgrounds". Using this approach, low-tillering QTLs were identified and validated base on an F6 recombinant inbred line population (MC population) derived from the low-tillering plant msf and Chuannong 16 (CN16), phenotypic data of effective tillers from multiple environments, and a 16K chip-based constructed genetic linkage map. QTL mapping results showed that there were four QTLs controlling tillering on chromosomes 1A, 5A, and 6D, respectively. Qltn.sau-MC-1A was a stable and major low-tillering QTL explaining 13.39%--60.40% of the phenotypic variation rate, and its positive allele was from msf. Phenotypic analysis showed that ETN of the lines carrying the positive allele of Qltn.sau-MC-1A was significantly less than those with the negative alleles. Correlation analysis showed that ETN had a significantly positive correlation with plant height (PH), and a significantly negative correlation with thousand kernel weight (TKW), kernel number per spike (KNPS), kernel weight per spike (KWPS), and flag leaf width (FLW), but no significantly correlation with flag leaf length (FLL) and anthesis date (AD). Genetic analysis showed that positive allele of Qltn.sau-MC-1A had a significant effect on increasing KNPS, KWPS, and TKW, but delaying AD. Validation results in different backgrounds suggested that the ETN of lines carrying positive alleles from Qltn.sau-MC-1A could be significantly decreased. Collectively, we established a new genetic mapping approach and further used it to identify and validate a major QTL controlling low-tiller number, Qltn.sau-MC-1A, which laid a foundation for further fine mapping and understanding the mechanism of tiller formation. [ABSTRACT FROM AUTHOR]