Combined Linkage and Association Mapping Reveals QTL and Candidate Genes for Plant and Ear Height in Maize

Abstract

Plant height (PH) and ear height (EH) are two very important agronomic traits related to the population density and lodging in maize. In order to better understand of the genetic basis of nature variation in PH and EH, two bi-parental populations and one genome-wide association study (GWAS) population were used to map quantitative trait loci (QTL) for both traits. Phenotypic data analysis revealed a wide normal distribution and high heritability for PH and EH in the three populations, which indicated that maize height is a highly polygenic trait. A total of 21 QTL for PH and EH in three common genomic regions (bin 1.05, 5.04/05, and 6.04/05) were identified by QTL mapping in the two bi-parental populations under multiple environments. Additionally, 41 single nucleotide polymorphisms (SNPs) were identified for PH and EH by GWAS, of which 29 SNPs were located in 19 unique candidate gene regions. Most of the candidate genes were related to plant growth and development. One QTL on Chromosome 1 was further verified in a near-isogenic line (NIL) population, and GWAS identified a C2H2 zinc finger family protein that maybe the candidate gene for this QTL. These results revealed that nature variation of PH and EH are strongly controlled by multiple genes with low effect and facilitated a better understanding of the underlying mechanism of height in maize.

Combined linkage and association mapping of putative QTLs controlling black tea quality and drought tolerance traits

“…The percentages of phenotypic variation explained (R 2 ) by various markers analysed using AM were significant as those analysed using MapQTL 6.0. This is in agreement with previous studies reported in plants on efficiency and robustness of combining linkage mapping and AM for precise identification of QTL (Mammadov et al 2015; Li et al 2016).…”

“…The integrated approach of linkage-AM has been used in other crop plants such as Arabidopsis (Sterken et al 2012), wheat (Shi et al 2017) and maize (Li et al 2016) to dissect quantitatively inherited traits. In tree species, an integrated method of linkage mapping and AM to decipher the nature of genetic architecture of potential QTLs for growth traits has been reported in poplar hybrids (Du et al 2016) and maritime pine (Bartholomé et al 2016).…”

Genome-wide association study (GWAS) reveals the genetic architecture of four husk traits in maize

“…Genome-wide association study (GWAS), which is based on genetic linkage disequilibrium (LD) in a panel including a large number of genotypes representing broadly natural variations, has been used as an alternative approach for exploring the molecular basis and identifying SNPs of complex quantitative traits [27–30]. In maize, GWAS has been successfully utilized to identify numerous candidate loci/genes controlling a serious of morphological or metabolic traits, such as drought tolerance [31], starch content [32], stalk cell wall components [33], plant height [34], herbivore-induced volatiles [35], male inflorescence size [36], shoot apical meristem size [37], etc.…”

Genetic‐based dissection of arsenic accumulation in maize using a genome‐wide association analysis method

“…In A. thaliana , GWAS and QTL mapping are used to complement each other, overcoming their individual limitations (Tiwari et al ., ). In maize, the combination of QTL mapping and GWAS has been used to identify candidate genes for plant ear height and ear traits (Li et al ., ; Xiao et al ., ). The combination of the two methods has also been applied to detect loci governing agronomic traits in other species, like soya bean (Zhao et al ., ) and rice (Lou et al ., ).…”