Combined linkage mapping and you may connection investigation is an effective way for examining the fresh new genetic structures off maize kernel faculties
Pick produce are a complex quantitative https://datingranking.net/escort-directory/athens/ characteristic. Knowing the hereditary design off maize produce contributes to high-yield breeding in the maize. QTL mapping and you will GWAS is one another effective equipment getting analysing the brand new hereditary structure out of quantitative faculties. QTL mapping might be always effectively choose the brand new chromosomal countries controlling collect agronomic qualities. GWAS facilitates the newest character away from quantitative characteristic nucleotides (QTNs) and you may applicant family genes regarding the target qualities. not, QTL mapping lies in linkage investigation that have biparental communities, which shows not enough hereditary assortment, and some hereditary loci do ergo getting shed. , 2006 ). Additionally, in some instances, alleles is unusual regarding diverse germplasm series in the association communities, and that honestly limit the function off GWAS to position QTL (Lu et al., 2010 ). Therefore, a combination of linkage and you may organization mapping is notably raise mapping show to possess decimal traits.
The main restricting foundation for GWAS is the determine of your own matchmaking of your own relationship committee, which results in brand new identity out of incorrect connectivity (Yu and Buckler, 2006 ; Yu et al
In this study, we utilized linkage and association mapping to detect QTL and candidate genes underlying grain yield in maize. By performing GWAS using the association panels, including 310 inbred lines with 39,354 SNP markers, we obtained 21 top significant SNPs (P < 2.25 ? 10 ?6 ) that were significantly associated with three kernel size traits in maize. For QTL mapping, the IBM Syn10 DH population with a higher genetic resolution than F2 and RIL populations and long genetic map length and high-density linkage marker is more suitable for QTL fine mapping of important traits (Holloway et al., 2011 ; Liu et al., 2015 ). In the present study, we conducted QTL analysis using the IBM Syn10 DH population including 265 lines and 6,618 bin markers and identified 50 QTL controlling the three kernel size traits of maize. The physical intervals of 32 of the 50 identified QTL were within 2 Mb, which was equivalent to fine mapping. A total of 56 identified SNPs by GWAS were located in 18 of the QTL mapped in the present study (Table S10). Therefore, these 18 QTL ent of molecular markers for high-yield breeding in maize.
Particular QTL handling maize kernel dimensions was in fact in past times seen by the linkage mapping or organization study using numerous communities. For example, Liu ainsi que al. ( 2017a ) understood 213 QTL getting maize kernel proportions attributes having fun with ten RIL populations (Liu mais aussi al., 2017a ). (mais…)