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ARS Home » Northeast Area » Ithaca, New York » Robert W. Holley Center for Agriculture & Health » Plant, Soil and Nutrition Research » Research » Publications at this Location » Publication #198149
Title: POWER TO DETECT HIGHER-ORDER EPISTATIC INTERACTIONS IN A METABOLIC PATHWAY USING NESTED ASSOCIATION MAPPING AND DIALLEL ASSOCIATION MAPPING

Author
item Buckler, Edward - Ed
item STICH, BENJAMIN - UNIV. OF HOHENHEIM
item YU, JIANMING - CORNELL UNIVERSITY
item MAURER, HANS - UNIV. OF HOHENHEIM
item MELCHINGER, ALBRECHT - UNIV. OF HOHENHEIM
item UTZ, H. FRIEDRICH - UNIV. OF HOHENHEIM

Submitted to: Genetics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/20/2006
Publication Date: 5/15/2007
Citation: Buckler Iv, E.S., Stich, B., Yu, J., Maurer, H.P., Melchinger, A.E., Utz, H. 2007. Power to detect higher-order epistatic interactions in a metabolic pathway using nested association mapping and diallel association mapping. Genetics. Vol. 176:563-570

Interpretive Summary: There are 50,000 genes in the maize genome, and these genes interact in complex ways to produce maize plants that grow in numerous environments and produce numerous products. However, there is a recurring problem that genetics has tremendous difficulty in identifying, which genes are interacting with one another. This research demonstrates the strengths and weaknesses of various genetic designs for identifying genetic interactions. These identified approaches are an improvement over existing approaches, but determining genetic interactions will still require large experiments.

Technical Abstract: Epistatic interactions among quantitative trait loci (QTL) contribute substantially to the variation in complex traits. The main objectives of this study were to (i) compare two- vs. four-step genome scans to identify four-way interactions among QTL belonging to a metabolic pathway, (ii) investigate by computer simulations the power and false discovery rate (FDR) of nested association mapping for detecting four-way interactions among QTL, and (iii) compare these estimates to those obtained for detecting four-way interactions among QTL using recombinant inbred line (RIL) populations derived from diallel and different partial diallel mating designs. The single nucleotide polymorphism haplotype data of B73 and 25 diverse maize inbreds were used to simulate the production of various RIL populations. Compared to the two-step genome scan, the power to detect four-way interactions was higher with the four-step genome scan. Higher power to detect four-way interactions was observed for RILs derived from optimally allocated distance-based designs than from nested designs or diallel designs. The power and FDR to detect four-way interactions using a nested design with 5000 RILs was for the 4 QTL scenario of a magnitude that seems promising for their identification.