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ARS Home » Midwest Area » East Lansing, Michigan » Sugarbeet and Bean Research » Research » Publications at this Location » Publication #116690

Title: GENE EXPRESSION ANALYSES TO IDENTIFY AND TARGET GENES FOR AGRONOMIC TRAITS, A CASE OF IMPROVING EMERGENCE IN SUGARBEET

Author
item Mcgrath, J Mitchell - Mitch
item Myers, Susan
item De Los Reyes, Benildo

Submitted to: Plant and Animal Genome Conference Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 1/10/2001
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: Field emergence and stand establishment are chronic problems for sugar beet growers, with an average of 50 plants surviving to harvest for every 100 seeds planted. Breeding for improved emergence has been problematic due to low heritability of the trait resulting in part from seed production environmental variation. Both biotic and abiotic stresses are involved in this seedling decline syndrome, but maximal field emergence seems consistently influenced by moisture availability. Field emergence counts show varietal differences, and we have used these differences to develop simple methods to dissect gene expression during sugar beet germination under various stress regimes. Differential display, subtractive hybridization, and random Expressed Sequence Tag (EST) sequencing have been used to scan for expressed genes that may explain differences between test conditions, and to extend this to differences between varieties. EST sequencing of 500 randomly selected cDNA clones derived from stressed germinating seeds showed a wide distribution of similarities with sequences in Genbank. Differential display only showed 5% of the ca. 900 fragments to differ between test conditions, and the range of similarities with known genes was less than ESTs. cDNA subtraction libraries showed an intermediate distribution of putative gene functions. These methods for revealing candidate genes are complementary, and the combination of subtracted cDNA libraries and differential display may be an effective approach towards building tools for more effective selection of traits with low heritability.