Detection of QTL for flowering time in multiple families of elite maize

Abstract

Flowering time is a fundamental quantitative trait in maize that has played a key role in the postdomestication process and the adaptation to a wide range of climatic conditions. Flowering time has been intensively studied and recent QTL mapping results based on diverse founders suggest that the genetic architecture underlying this trait is mainly based on numerous small-effect QTL. Here, we used a population of 684 progenies from five connected families to investigate the genetic architecture of flowering time in elite maize. We used a joint analysis and identified nine main effect QTL explaining approximately 50 % of the genotypic variation of the trait. The QTL effects were small compared with the observed phenotypic variation and showed strong differences between families. We detected no epistasis with the genetic background but four digenic epistatic interactions in a full 2-dimensional genome scan. Our results suggest that flowering time in elite maize is mainly controlled by main effect QTL with rather small effects but that epistasis may also contribute to the genetic architecture of the trait.

Mapping QTL for agronomic traits in breeding populations

“…epistasis. Steinhoff et al (2012) showed that such differences in allele substitution effects are more likely to arise due to multiple alleles at a QTL locus or due to differences in allele frequencies between families. Allele frequencies are affected by segregation distortion that can arise due to selection (McMullen et al 2009;Alheit et al 2011), but are also subject to the sampling process especially if family sizes are small (Fig.…”

“…The most promising approach to detect epistatic QTL appears to be a full two-dimensional scan for all possible pairwise interactions. Such scans are nowadays computationally feasible and have successfully been used to detect epistatic interactions in family mapping (e.g., Buckler et al 2009;Liu et al 2011;Steinhoff et al 2012;Würschum et al 2012c), and in population mapping (e.g., Li et al 2010;Massman et al 2011;Reif et al 2011;Würschum et al 2011a, b;Yu et al 2011).…”

Comparative quantitative trait locus mapping of maize flowering-related traits in an F2:3 and recombinant inbred line population

“…Some related genes have been identified, including VGT1 (vegetative to generative transition 1) (Salvi et al, 2002;Salvi et al, 2007). QTL mapping results have been obtained from many different genetic backgrounds and are useful for understanding flowering-related traits (Beavis et al, 1994;Li et al, 2007;Buckler et al, 2009;Steinhoff et al, 2012;Mace et al, 2013).…”

Mapeamento de QTL para múltiplos caracteres e ambientes em milho

“…(Veldboom et al 1994). Como os QTL mapeados não identificam genes, mas sim regiões cromossômicas que podem incluir vários QTL, dada a ocorrência de múltiplos alelos, os graus de dominância podem variar de acordo com a combinação dos alelos e dos genes e, assim, essas variações podem explicar as divergências observadas na literatura quanto ao grau de dominância dos QTL (Steinhoff et al 2012).…”

“…Ainda, um mesmo QTL pode ser mapeado em posições diferentes nos cromossomos, devido à existência de segmentos duplicados nos cromossomos do milho e aos níveis de incerteza inerentes aos processos de mapeamento (Campos et al 2004 (Steinhoff et al 2012). Ademais, a metodologia empregada no mapeamento considera apenas um QTL por intervalo de marcadores (Jiang e Zeng 1995).…”