Mapping of dynamic QTLs for resistance to Fusarium wilt (Fusarium oxysporum f. sp. vasinfectum) race 4 in a backcross inbred line population of Upland cotton.

Abstract

A backcross inbred line population of cotton was evaluated for Fusarium wilt race 4 resistance at different days after inoculation (DAI). Both constitutively expressed and developmentally regulated QTLs were detected. The soil-borne fungus Fusarium oxysporum f. sp. vasinfectum (FOV) race 4 (FOV4) causes Fusarium wilt including seedling mortality in cotton. A backcross inbred line (BIL) population of 181 lines, derived from a bi-parental cross of moderately resistant non-recurrent Hai 7124 (Gossypium barbadense) and recurrent parent CCRI 36 (G. hirsutum), was evaluated under temperature-controlled conditions for FOV4 resistance with artificial inoculations. Based on three replicated tests evaluated at 7, 14, 21, and 28days after inoculation (DAI), only 2-5 BILs showed lower disease severity ratings (DSR) than the parents while 22-50 BILs were more susceptible, indicating transgressive segregation toward susceptibility. Although DSR were overall congruent between DAI, there were many BILs displaying different responses to FOV4 across DAI. Genetic mapping using 7709 SNP markers identified 42 unique QTLs for four evaluation parameters- disease incidence (DI), DSR, mortality rate (MR), and area under disease progress curve (AUDPC), including 26 for two or more parameters. All five QTLs for AUDPC were co-localized with QTLs for DI, DSR, and/or MR at one or two DAI, indicating the unnecessary use of AUDPC in QTL mapping for FOV4 resistance. Those common QTLs explained the significant positive associations between parameters observed. Ten common QTLs with negative or positive additive effects were detected between DAI. DAI-specific and consistent QTLs were detected between DAI in cotton for the first time, suggesting the existence of both constitutively expressed and developmentally regulated QTLs for FOV4 resistance and the importance of evaluating genetic populations for FOV4 resistance at different growth stages.