QTL Analysis for Transgressive Resistance to Root-Knot Nematode in Interspecific Cotton ( Gossypium spp.) Progeny Derived from Susceptible Parents

Abstract

The southern root-knot nematode (RKN, Meloidogyne incognita) is a major soil-inhabiting plant parasite that causes significant yield losses in cotton ( Gossypium spp.). Progeny from crosses between cotton genotypes susceptible to RKN produced segregants in subsequent populations which were highly resistant to this parasite. A recombinant inbred line (RIL) population of 138 lines developed from a cross between Upland cotton TM-1 ( G. hirsutum L.) and Pima 3–79 ( G. barbadense L.), both susceptible to RKN, was used to identify quantitative trait loci (QTLs) determining responses to RKN in greenhouse infection assays with simple sequence repeat (SSR) markers. Compared to both parents, 53.6% and 52.1% of RILs showed less ( P<0.05) root-galling index (GI) and had lower ( P<0.05) nematode egg production (eggs per gram root, EGR). Highly resistant lines (transgressive segregants) were identified in this RIL population for GI and/or EGR in two greenhouse experiments. QTLs were identified using the single-marker analysis nonparametric mapping Kruskal-Wallis test. Four major QTLs located on chromosomes 3, 4, 11, and 17 were identified to account for 8.0 to 12.3% of the phenotypic variance ( R ² ) in root-galling. Two major QTLs accounting for 9.7% and 10.6% of EGR variance were identified on chromosomes 14 and 23 ( P<0.005), respectively. In addition, 19 putative QTLs ( P<0.05) accounted for 4.5–7.7% of phenotypic variance ( R ² ) in GI, and 15 QTLs accounted for 4.2–7.3% of phenotypic variance in EGR. In lines with alleles positive for resistance contributed by both parents in combinations of two to four QTLs, dramatic reductions of >50% in both GI and EGR were observed. The transgressive segregants with epistatic effects derived from susceptible parents indicate that high levels of nematode resistance in cotton may be attained by pyramiding positive alleles using a QTL mapping approach.