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Title: Genetic mapping of FAD2 genes and their relative contribution towards oil quality in peanut (Arachis hypogaea L.)

item PANDEY, MANISH - University Of Georgia
item WANG, HUI - University Of Georgia
item QIAO, LIXIAN - University Of Georgia
item FENG, SUPING - University Of Georgia
item KHERA, PAWAN - University Of Georgia
item CULBREATH, ALBERT - University Of Georgia
item Wang, Ming
item Anglin, Noelle
item WANG, JIANPING - University Of Florida
item Holbrook, Carl - Corley
item VARSHNEY, RAJEEV - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India
item Guo, Baozhu

Submitted to: American Peanut Research and Education Society Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: 6/1/2014
Publication Date: 6/20/2014
Citation: Pandey, M., Wang, H., Qiao, L., Feng, S., Khera, P., Culbreath, A., Wang, M.L., Barkley, N.L., Wang, J., Holbrook Jr, C.C., Varshney, R., Guo, B. 2014. Genetic mapping of FAD2 genes and their relative contribution towards oil quality in peanut (Arachis hypogaea L.) [abstract]. American Peanut Research and Education Society.

Interpretive Summary:

Technical Abstract: Improvement of oil quality is the major research objective in peanut because of its high economic impact on growers/traders and several health benefits to consumers. Fatty acid desaturase (FAD) genes are known to control quality traits but their position on the peanut genome and their relative contribution towards total phenotypic variance for these quality traits is still a mystery. In this context, two improved genetic maps using S-population (SunOleic 97R × NC94022) and T-population (Tifrunner × GT-C20) were developed with 206 (1780.6 cM) and 377 (2487.4 cM) marker loci and marker density of 9.6 and 7.6 cM/marker loci, respectively. Quantitative trait loci (QTL) analysis for oleic acid, linoleic acid, oleic / linoleic acid ratio and oil content detected a total of 41 and 49 main-effect QTLs (M-QTLs) explaining upto 45.63% and 39.50% phenotypic variance (PV) using QTL Cartographer for S- and T-population, respectively. Similarly, QTLNetwork identified 11 M-QTLs each for S- and T-population with PV upto 25.42% and 29.13%, respectively. In case of epistatic QTLs (E-QTLs), QTLNetwork detected eight E-QTLs in S-population and two E-QTLs in T-population with PV upto 2.83 and 2.19%, respectively. Mutant allele FAD2A contributed upto 9.11% and 38.41% of PV in S- and T-population, respectively while FAD2B contributed 42.33% PV in S-population. The phenotypic effect of M-QTLs and E-QTLs detected through QTLNetwork showed lower PV as compared to M-QTLs detected from QTL Cartographer. More importantly PV of FAD2 genes for oleic acid, linoleic acid and O/L ratio were estimated in addition to mapping these genes. Now, it is clear that contribution of FAD2B is higher than the FAD2A gene in controlling quality traits. In summary, present study lead to development of two improved genetic maps and identification of 112 M-QTLs and 10 E-QTLs for oil quality traits. The information generated through present study is very useful for marker-assisted accelerated improvement of peanut oil quality.