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ARS Home » Southeast Area » Raleigh, North Carolina » Plant Science Research » Research » Publications at this Location » Publication #275721
Title: Mining natural variation for maize improvement: Selection on phenotypes and genes

Author
item SOOD, SHILPA - North Carolina State University
item Flint-Garcia, Sherry
item WILLCOX, MARTHA - International Maize & Wheat Improvement Center (CIMMYT)
item Holland, Jim - Jim

Submitted to: Book Chapter
Publication Type: Book / Chapter
Publication Acceptance Date: 7/24/2012
Publication Date: 1/6/2014
Citation: Sood, S., Flint Garcia, S.A., Willcox, M., Holland, J.B. 2014. Mining natural variation for maize improvement: Selection on phenotypes and genes. In: R. Tuberosa et al. (eds.), Genomics of Plant Genetic Resources. p. 615 – 649.

Interpretive Summary: Maize is very diverse. Tropical maize and teosinte are important genetic resources that harbor unique genes not found in corn hybrids grown by farmers in the USA. To access these resources, breeders must be able to extract favorable genes from tropical maize and teosinte. Long-term traditional breeding efforts have demonstrated the value of diverse germplasm to improve maize productivity, while also enhancing the genetic base of cultivated varieties. Genomics provides new opportunities to identify the genes affecting important agronomic traits and to estimate the wide range of allelic effects at such genes. New approaches to complex trait analysis, including joint multiple population analysis, genome-wide association analysis, and genomic selection, can leverage high throughput sequencing and genotyping technologies to improve our understanding of the genome-wide distribution of allele effects across the wide genetic variation in the primary gene pool of maize. Implementing this information for practical maize improvement remains a challenge.

Technical Abstract: Maize is highly genetically and phenotypically diverse. Tropical maize and teosinte are important genetic resources that harbor unique alleles not found in temperate maize hybrids. To access these resources, breeders must be able to extract favorable unique alleles from tropical maize and teosinte from their population genomic context, where they are linked with many undesired alleles that confer adaptation to tropical environments, ancient farming methods, or wild growth habit (in the case of teosinte). Long-term traditional breeding efforts have demonstrated the value of diverse germplasm to improve maize productivity, while also enhancing the genetic base of cultivated varieties. Genomics provides new opportunities to identify the genes affecting important agronomic traits and to estimate the wide range of allelic effects at such genes. New approaches to complex trait analysis, including joint multiple population analysis, genome-wide association analysis, and genomic selection, can leverage high throughput sequencing and genotyping technologies to improve our understanding of the genome-wide distribution of allele effects across the wide genetic variation in the primary gene pool of maize. Implementing this information for practical maize improvement remains a challenge.