A method called MutMap was developed to identify genes responsible for agronomically important traits in rice. This method uses whole-genome resequencing of pooled DNA from a segregating population of plants with a useful phenotype. MutMap involves crossing a mutant to the original wild-type line and selfing the offspring to allow clear segregation of subtle phenotypic differences. This approach is efficient for crops as it minimizes the number of genetic crosses and mutant F2 progeny required. The method was applied to seven mutants of a Japanese rice cultivar to identify genomic regions likely harboring mutations causing pale green leaves and semidwarfism, an important agronomic trait. The results show that MutMap can accelerate the genetic improvement of rice and other crops. The world population is expected to reach 9 billion in 40 years, requiring a significant increase in food production. Ensuring sustainable food production without expanding farmland is a major challenge. Crop breeding is crucial for improving yield and tolerance to stresses, but current methods are inefficient and have not fully incorporated genomic findings. Most agronomic traits are controlled by multiple genes, including quantitative trait loci (QTL), which cause minor phenotypic effects. Identifying the loci responsible for these traits is important for marker-assisted selection. However, subtle changes in phenotype make cloning these genes difficult. MutMap was used to identify genes controlling agronomically important traits in rice. It was applied to pale green leaf mutants, and the method successfully identified genomic regions likely harboring mutations. For example, in the Hit1917-pl1 mutant, a mutation in the OsCAO1 gene was identified, which is responsible for the pale green leaf phenotype. Complementation studies confirmed that the mutation in OsCAO1 caused the phenotype. MutMap was also applied to semidwarf mutants and a male sterile mutant, identifying genomic regions responsible for these traits. The method was found to be effective in identifying causal mutations for various traits, even when the phenotypic changes are subtle. MutMap is technically similar to other methods like SHOREmap and NGM, but it uses SNPs from mutagenesis as markers rather than SNPs between different ecotypes. This makes MutMap more practical for crops with long generation times and large genomes. The method can be simplified for traits easily quantifiable in the field, reducing the need for extensive crosses. MutMap has the potential to significantly reduce the time and labor required to identify agronomically important genes, making it a valuable tool for crop breeding. As DNA sequencing becomes more affordable, the cost of identifying such genes could be significantly reduced. MutMap can also be used for marker-assisted selection without identifying the exact causal mutation, by using SNPs flanking the regions harboring the mutations. This approach can help breeders develop new varieties of crops.A method called MutMap was developed to identify genes responsible for agronomically important traits in rice. This method uses whole-genome resequencing of pooled DNA from a segregating population of plants with a useful phenotype. MutMap involves crossing a mutant to the original wild-type line and selfing the offspring to allow clear segregation of subtle phenotypic differences. This approach is efficient for crops as it minimizes the number of genetic crosses and mutant F2 progeny required. The method was applied to seven mutants of a Japanese rice cultivar to identify genomic regions likely harboring mutations causing pale green leaves and semidwarfism, an important agronomic trait. The results show that MutMap can accelerate the genetic improvement of rice and other crops. The world population is expected to reach 9 billion in 40 years, requiring a significant increase in food production. Ensuring sustainable food production without expanding farmland is a major challenge. Crop breeding is crucial for improving yield and tolerance to stresses, but current methods are inefficient and have not fully incorporated genomic findings. Most agronomic traits are controlled by multiple genes, including quantitative trait loci (QTL), which cause minor phenotypic effects. Identifying the loci responsible for these traits is important for marker-assisted selection. However, subtle changes in phenotype make cloning these genes difficult. MutMap was used to identify genes controlling agronomically important traits in rice. It was applied to pale green leaf mutants, and the method successfully identified genomic regions likely harboring mutations. For example, in the Hit1917-pl1 mutant, a mutation in the OsCAO1 gene was identified, which is responsible for the pale green leaf phenotype. Complementation studies confirmed that the mutation in OsCAO1 caused the phenotype. MutMap was also applied to semidwarf mutants and a male sterile mutant, identifying genomic regions responsible for these traits. The method was found to be effective in identifying causal mutations for various traits, even when the phenotypic changes are subtle. MutMap is technically similar to other methods like SHOREmap and NGM, but it uses SNPs from mutagenesis as markers rather than SNPs between different ecotypes. This makes MutMap more practical for crops with long generation times and large genomes. The method can be simplified for traits easily quantifiable in the field, reducing the need for extensive crosses. MutMap has the potential to significantly reduce the time and labor required to identify agronomically important genes, making it a valuable tool for crop breeding. As DNA sequencing becomes more affordable, the cost of identifying such genes could be significantly reduced. MutMap can also be used for marker-assisted selection without identifying the exact causal mutation, by using SNPs flanking the regions harboring the mutations. This approach can help breeders develop new varieties of crops.