Genetic Property Of 24 Parents MAGIC Population And Its Applications In Complex Quantitative Traits

Maize(Zea mays L.),is an important source of human food,livestock feed and industrial raw materials.Through the genetic improvement,the combination of molecular breeding and traditional breeding is of great significance to improve maize yield.As for maize traits,almost important agronomic and yield traits are complex quantitative traits,which are controlled by multiple minor alleles.The integration of ideal mapping population and high density genotype will promote the understanding of genetic basis of complex traits.In this research,a multi-parent advanced generation intercross(MAGIC)population,was used for systematically illustrating the genetic basis of 20 quantitative traits by single variant genome-wide association study(svGWAS)and haplotype genome-wide association study(hapGWAS).The main results are summarized as follows.1 Phenotypic variations of MAGIC populationThe MAGIC population were grown in five environments at different latitudes in the summer of 2014,and 3 flowering traits,8 agronomic traits and 9 yield-related traits data in each environment were collected.Most traits were in normal distribution,and have high correlations in any two environments.The coefficient of variation for these traits were 3.13%-36.13%,with the mean of 12.98%.The broad sense heritability of the traits was ranged from 73.11%to 92.68%,with the mean of 83.93%.2 Genome feature of MAGIC populationIllumina sequence technology was applied for genome resequencing,with 11×coverage for parents and 1× coverage for the offspring.A total of 53.5 million SNPs were obtained,out of which there were 36.1 million SNPs with minor allele frequency(MAF)more than 0.02.Principal component analysis showed MAGIC population has weak population structure.At the level of r2 equal to 0.1,LD decay estimation of parents was 230kb and that of the offspring was 20kb,suggested a great number of recombination events occurred in the population.The Hidden Markov Model was used to construct a mosaic haplotype map.A total of 319,285 recombination events were captured in the offspring,and 227 recombination events occurred in each line on average.By combining all the haplotypes,30,350 minimum recombination bins(unique bin)were utilized for hapGWAS.The average size of unique bin was 80kb,and the distance between two adjacent unique bin was 50bp.The contributions of the haplotype inherited from parents were biased in the offspring genome,ranging from 0.70%to 12.50%.The contributions from two parents(HUANGC and ZOGN31)were over 10%,and the contribution from two parents(5237 and HYS)just accounted for less than 2%.3 QTL number and effectsA total of 443 QTLs were detected for 20 traits in this study.The QTL number for each trait varied from 12 to 33,with an average of 22.There were 37 QTLs contained only single gene.The phenotypic variation rate(R2)explained by each single QTL was 0.15%-18.2%,with an average of 5.98%.The R2 of 35 loci for 11 traits were more than 10%.Combined explanation for each trait variation was ranged from 41.10%to 71.88%,with the mean of 59.79%.32 QTLs contained the known genes,such as flowering time related gene ZCN8,plant height related gene brd1,inflorescence related gene ub3.26 QTLs contained the candidate genes in previous studies,and 66 QTLs were overlapped with the reported ones.The remaining 319 QTLs were the novel identified in this study.4 Comparison between svGWAS and hapGWASTwo mapping methods,svGWAS and hapGWAS were applied for QTL mapping.A total of 443 QTLs were detected,and 35 out of them were detected consistently in both mapping methods.105 QTLs were uniquely identified by svGWAS,and 303 QTLs were particular for hapGWAS.Compared with svGWAS,hapGWAS is much more powerful not only at detecting QTLs but also at explaining phenotypic variation(R2).The average R2 explained by single QTL of svGWAS and hapGWAS was 4.29%and 6.63%,respectively.The combined R2 explained by QTLs of svGWAS and hapGWAS was 21.46%and 66.59%,respectively.The combined phenotypic variation explained by hapGWAS was more than that by svGWAS.For svGWAS,significant SNPs were mainly enriched in 5’UTR,3’UTR and exon regions,and less in far genic region.Synonymous variants were also enriched.The R2 of the genic region was slightly higher than that of the intergenic region,and the number of large effect loci was also more than that of the intergenic region.The MAF for all the peak SNPs for each QTLs in svGWAS were 0.02-0.49,with the mean of 0.27.A negative correlation between MAF and additive effect(r=-0.42,P=1.73E-07),suggested that large effect loci were the rare variants.5 Fine mapping and genetic analysis for a major QTL of ear leaf widthWe performed further analysis for one QTL of ear leaf width.This QTL located in chr4:1.99Mb-4,84Mb,with R2 of 18.2%,and additive effect of 0.68cm.The haplotype from HUANGC showed negative effect which helped us to divide the parents into HUANGC and NON-HUANGC groups,and successfully narrow down the QTL to an interval of 338,836bp which contained 15 candidate genes.Combining of SNP variation function,RNA-seq and metabolites of 71 extreme lines,we focused on one gene which encoded galactose oxidase.Further verification of this gene is in progress.