A differentially methylated region of the ZmCCT10 promoter affects flowering time in hybrid maize

Flowering time(FT) is a key maize domestication trait, variation in which allows maize to grow in a wide range of latitudes. Although previous studies have investigated the genetic control of FT-related traits per se, few studies of FT hybrid performance have been published. We characterized the genomic architecture associated with hybrid performance for FT in a hybrid panel by testcrossing Chang 7–2 with 328Ye478 × Qi319 recombinant inbred lines(RILs). We identified 11 quantitative trait loci(QTL) for hybrid performance in FT-related traits, including a major QTL qFH10 that controls hybrid performance and heterosis in a summer maize-growing region. However, this locus acts in regulating FT traits per se only in a spring maize-growing region. We validated ZmCCT10 as a candidate gene for qFH10 and found that differences between hybrids and their parental lines in DNA methylation in the differentially methylated region(DMR, –700 to –1520) of the ZmCCT10 promoter affected gene expression pattern and thereby FT in the summer maize-growing region.

Genomic prediction of yield performance among single-cross maize hybrids using a partial diallel cross design

Genomic prediction(GP)in plant breeding has the potential to predict and identify the best-performing hybrids based on the genotypes of their parental lines.In a GP experiment,34 elite inbred lines were selected to make 285 single-cross hybrids in a partial-diallel cross design.These lines represented a mini-core collection of Chinese maize germplasm and comprised 18 inbred lines from the Stiff Stalk heterotic group and 16 inbred lines from the Non-Stiff Stalk heterotic group.The parents were genotyped by sequencing and the 285 hybrids were phenotyped for nine yield and yield-related traits at two locations in the summer sowing area(SUS)and three locations in the spring sowing area(SPS)in the main maizeproducing regions of China.Multiple GP models were employed to assess the accuracy of trait prediction in the hybrids.By ten-fold cross-validation,the prediction accuracies of yield performance of the hybrids estimated by the genomic best linear unbiased prediction(GBLUP)model in SUS and SPS were 0.51 and 0.46,respectively.The prediction accuracies of the remaining yield-related traits estimated with GBLUP ranged from 0.49 to 0.86 and from 0.53 to 0.89 in SUS and SPS,respectively.When additive,dominance,epistasis effects,genotype-by-environment interaction,and multi-trait effects were incorporated into the prediction model,the prediction accuracy of hybrid yield performance was improved.The ratio of training to testing population and size of training population optimal for yield prediction were determined.Multiple prediction models can improve prediction accuracy in hybrid breeding.

Genetic characterization and linkage disequilibrium mapping of resistance to gray leaf spot in maize(Zea mays L.)

Gray leaf spot(GLS),caused by Cercospora zeae-maydis,is an important foliar disease of maize(Zea mays L.)worldwide,resistance to which is controlled by multiple quantitative trait loci(QTL).To gain insights into the genetic architecture underlying the resistance to this disease,an association mapping population consisting of 161 inbred lines was evaluated for resistance to GLS in a plant pathology nursery at Shenyang in 2010 and 2011.Subsequently,a genome-wide association study,using 41,101 single-nucleotide polymorphisms(SNPs),identified 51 SNPs significantly(P<0.001)associated with GLS resistance,which could be converted into 31 QTL.In addition,three candidate genes related to plant defense were identified,including nucleotidebinding-site/leucine-rich repeat,receptor-like kinase genes similar to those involved in basal defense.Two genic SNPs,PZE-103142893 and PZE-109119001,associated with GLS resistance in chromosome bins 3.07 and 9.07,can be used for marker-assisted selection(MAS)of GLS resistance.These results provide an important resource for developing molecular markers closely linked with the target trait,enhancing breeding efficiency.

Identification of Functional Genetic Variations Underlying Drought Tolerance in Maize Using SNP Markers

Single nucleotide polymorphism （SNP） is a common form of genetic variation and popularly exists in maize genome. An Illumina GoldenGate assay with 1 536 SNP markers was used to genotype maize inbred lines and identified the functional genetic variations underlying drought tolerance by association analysis. Across 80 lines, 1 006 polymorphic SNPs （65.5% of the total） in the assay with good call quality were used to estimate the pattern of genetic diversity, population structure, and familial relatedness. The analysis showed the best number of fixed subgroups was six, which was consistent with their original sources and results using only simple sequence repeat markers. Pairwise linkage disequilibrium （LD） and association mapping with phenotypic traits investigated under water-stressed and well-watered regimes showed rapid LD decline within 100–500 kb along the physical distance of each chromosome, and that 29 SNPs were associated with at least two phenotypic traits in one or more environments, which were related to drought-tolerant or drought-responsive genes. These drought-tolerant SNPs could be converted into functional markers and then used for maize improvement by marker-assisted selection.