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ARS Home » Southeast Area » Tifton, Georgia » Crop Protection and Management Research » Research » Publications at this Location » Publication #340506

Title: Nested association mapping for dissecting complex traits using Peanut 58K SNP array

Author
item AGARWAL, GAURAV - University Of Georgia
item WANG, HUI - University Of Georgia
item CHUDHARY, DIYA - University Of Georgia
item CULBREATH, ALBERT - University Of Georgia
item PANDEY, MANISH - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India
item VARSHNEY, RAJEEV - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India
item CHU, YE - University Of Georgia
item OZIAS-AKINS, PEGGY - University Of Georgia
item ISLEIB, TOM - North Carolina State University
item Holbrook, Carl - Corley
item Guo, Baozhu

Submitted to: American Peanut Research and Education Society Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: 5/1/2017
Publication Date: 7/11/2017
Citation: Agarwal, G., Wang, H., Chudhary, D., Culbreath, A., Pandey, M., Varshney, R., Chu, Y., Ozias-Akins, P., Isleib, T., Holbrook Jr, C.C., Guo, B. 2017. Nested association mapping for dissecting complex traits using Peanut 58K SNP array [abstract]. American Peanut Research and Education Society Abstracts.

Interpretive Summary:

Technical Abstract: Genome-wide association studies (GWAS) and linkage mapping have been the two most predominant strategies to dissect complex traits, but are limited by the occurrence of false positives reported for GWAS, and low resolution in the case of linkage analysis. This has led to the development of a joint approach, nested association mapping (NAM). The US peanut community has developed 16 structured and interrelated RIL populations using a 2 x 8 (common x unique) factorial nested mating association mapping design. Parents were selected in an attempt to maximize genetic diversity while meeting practical breeding objectives. Our objective is to test if the NAM strategy has increased power for QTL detection since NAM uses multiple linkage mapping populations resulting in better QTL resolution without false positives. In the current study, we used eight of these structured cross combinations (Set A) (Tifrunner x N08082olJCT; Tifrunner x SPT 06-06; Tifrunner x C76-16; Tifrunnner x NC 3033; Florida-07 x N08082olJCT; Florida-07 x SPT 06-06; Florida-07 x C76-16; and Florida-07 x NC 3033) to dissect the complex traits. A total of 1090 RILs of these two NAM populations (a sub-set of each NAM, 600 and 490 RILs, respectively) from this collection, with one common and four founder parents for each of the two populations were investigated. The common parents are Tifrunner and Florida-07. A total of 3,596 unique highly polymorphic SNPs (chi-squared test p < 0.05, and less than 20% missing data) were obtained from the Peanut 58K SNP array, and have been used to develop a consensus linkage map for each of the two populations. Initially, individual linkage maps for each population were constructed followed by a consensus map using the common SNPs from the populations. With the availability of multiple seasons of phenotyping data for morphological (main stem height, plant size, leaf length and width), disease-related (Tomato spotted wilt virus and leaf spots), and seed traits, QTL analyses of the NAM populations will yield greater resolution of the genomic regions responsible for governing these complex traits. This study will provide directions and resources for the peanut community to identify detailed positions of genes controlling peanut morphology and disease resistance along with other studies of individual RILs.