Dataset Information

Genomic Dissection of Leaf Angle in Maize (Zea mays L.) Using a Four-Way Cross Mapping Population.

ABSTRACT: Increasing grain yield by the selection for optimal plant architecture has been the key focus in modern maize breeding. As a result, leaf angle, an important determinant of plant architecture, has been significantly improved to adapt to the ever-increasing plant density in maize production over the past several decades. To extend our understanding on the genetic mechanisms of leaf angle in maize, we developed the first four-way cross mapping population, consisting of 277 lines derived from four maize inbred lines with varied leaf angles. The four-way cross mapping population together with the four parental lines were evaluated for leaf angle in two environments. In this study, we reported linkage maps built in the population and quantitative trait loci (QTL) on leaf angle detected by inclusive composite interval mapping (ICIM). ICIM applies a two-step strategy to effectively separate the cofactor selection from the interval mapping, which controls the background additive and dominant effects at the same time. A total of 14 leaf angle QTL were identified, four of which were further validated in near-isogenic lines (NILs). Seven of the 14 leaf angle QTL were found to overlap with the published leaf angle QTL or genes, and the remaining QTL were unique to the four-way population. This study represents the first example of QTL mapping using a four-way cross population in maize, and demonstrates that the use of specially designed four-way cross is effective in uncovering the basis of complex and polygenetic trait like leaf angle in maize.

SUBMITTER: Ding J

PROVIDER: S-EPMC4625009 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Leaf angle is an important agronomic trait in maize [Zea mays L.]. The compact plant phenotype, with a smaller leaf angle, is suited for high-density planting and thus for increasing crop yields. Here, we studied the ethyl methane sulfonate (EMS)-induced mutant bhlh112. Leaf angle and plant height were significantly decreased in bhlh112 compared to the wild-type plants. After treatment of seedlings with exogenous IAA and ABA respectively, under the optimal concentration of exogenous hormones, the variation of leaf angle of the mutant was more obvious than that of the wild-type, which indicated that the mutant was more sensitive to exogenous hormones. Transcriptome analysis showed that the ZmbHLH112 gene was related to the biosynthesis of auxin and brassinosteroids, and involved in the activation of genes related to the auxin and brassinosteroid signal pathways as well as cell elongation. Among the GO enrichment terms, we found many differentially expressed genes (DEGs) enriched in the cell membrane and ribosomal biosynthesis, hormone biosynthesis and signaling pathways, and flavonoid biosynthesis, which could influence cell growth and the level of endogenous hormones affecting leaf angle. Therefore, ZmbHLH112 might regulate leaf angle development through the auxin signaling and the brassinosteroid biosynthesis pathways. 12 genes related to the development of leaf were screened by WGCNA; In GO enrichment and KEGG pathways, the genes were mainly enriched in rRNA binding, ribosome biogenesis, Structural constituent of ribosome; Arabidopsis ribosome RNA methyltransferase CMAL is involved in plant development, likely by modulating auxin derived signaling pathways; The free 60s ribosomes and polysomes in the functional defective mutant rice minute-like1 (rml1) were significantly reduced, resulting in plant phenotypic diminution, narrow leaves, and growth retardation; Hence, ribosomal subunits may play an important role in leaf development. These results provide a foundation for further elucidation of the molecular mechanism of the regulation of leaf angle in maize.

Project description:Common rust is one of the major foliar diseases in maize, leading to significant grain yield losses and poor grain quality. To dissect the genetic architecture of common rust resistance, a genome-wide association study (GWAS) panel and a bi-parental doubled haploid (DH) population, DH1, were used to perform GWAS and linkage mapping analyses. The GWAS results revealed six single-nucleotide polymorphisms (SNPs) significantly associated with quantitative resistance of common rust at a very stringent threshold of P-value 3.70 × 10-6 at bins 1.05, 1.10, 3.04, 3.05, 4.08, and 10.04. Linkage mapping identified five quantitative trait loci (QTL) at bins 1.03, 2.06, 4.08, 7.03, and 9.00. The phenotypic variation explained (PVE) value of each QTL ranged from 5.40 to 12.45%, accounting for the total PVE value of 40.67%. Joint GWAS and linkage mapping analyses identified a stable genomic region located at bin 4.08. Five significant SNPs were only identified by GWAS, and four QTL were only detected by linkage mapping. The significantly associated SNP of S10_95231291 detected in the GWAS analysis was first reported. The linkage mapping analysis detected two new QTL on chromosomes 7 and 10. The major QTL on chromosome 7 in the region between 144,567,253 and 149,717,562 bp had the largest PVE value of 12.45%. Four candidate genes of GRMZM2G328500, GRMZM2G162250, GRMZM2G114893, and GRMZM2G138949 were identified, which played important roles in the response of stress resilience and the regulation of plant growth and development. Genomic prediction (GP) accuracies observed in the GWAS panel and DH1 population were 0.61 and 0.51, respectively. This study provided new insight into the genetic architecture of quantitative resistance of common rust. In tropical maize, common rust could be improved by pyramiding the new sources of quantitative resistance through marker-assisted selection (MAS) or genomic selection (GS), rather than the implementation of MAS for the single dominant race-specific resistance gene.

Dataset Information

Genomic Dissection of Leaf Angle in Maize (Zea mays L.) Using a Four-Way Cross Mapping Population.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets