Genome-wide association studies and genomic selection for leaf-related traits in maize

Area of Science:

• Plant genetics and breeding
• Agricultural science
• Genomics

Background:

• Leaf morphology significantly impacts maize plant architecture, photosynthesis, and grain yield.
• Understanding the genetic basis of leaf traits is crucial for effective breeding strategies.
• Genomic selection (GS) offers a powerful approach to accelerate crop improvement.

Purpose of the Study:

• To perform a genome-wide association study (GWAS) and GS for maize leaf-related traits.
• To identify significant single nucleotide polymorphisms (SNPs) and candidate genes controlling leaf length, width, area, and number.
• To determine optimal parameters for GS application in maize leaf trait breeding.

Main Methods:

• Phenotyped a natural maize population (291 inbred lines) across four environments for various leaf traits.
• Genotyped the population using sequencing and performed GWAS with FarmCPU and BLINK models.
• Applied GS to assess prediction accuracy and identify optimal training population size and SNP set.

Main Results:

• Identified 24, 34, 14, and 19 unique significant SNPs for leaf length, width, area (LAr2), and leaf number above ear (LNAE), respectively.
• Discovered 11 pleiotropic SNPs affecting multiple leaf traits, suggesting common genetic control.
• Highlighted five key candidate genes (e.g., Zm00001eb297330) and found 70% training population and 3000 SNPs are adequate for GS.

Conclusions:

• This research elucidates the genetic architecture of maize leaf traits.
• Identified significant SNPs and candidate genes provide valuable targets for marker-assisted selection.
• The study validates GS as an effective tool for accelerating breeding programs focused on improving maize leaf morphology and yield.