title: Identification of several small main-effect QTLs and a large number of epistatic QTLs for drought tolerance related traits in groundnut (Arachis hypogaea L.).
abstract: Cultivated groundnut or peanut (Arachis hypogaea L.), an allotetraploid (2n = 4x = 40), is a self pollinated and widely grown crop in the semi-arid regions of the world. Improvement of drought tolerance is an important area of research for groundnut breeding programmes. Therefore, for the identification of candidate QTLs for drought tolerance, a comprehensive and refined genetic map containing 191 SSR loci based on a single mapping population (TAG 24 x ICGV 86031), segregating for drought and surrogate traits was developed. Genotyping data and phenotyping data collected for more than ten drought related traits in 2-3 seasons were analyzed in detail for identification of main effect QTLs (M-QTLs) and epistatic QTLs (E-QTLs) using QTL Cartographer, QTLNetwork and Genotype Matrix Mapping (GMM) programmes. A total of 105 M-QTLs with 3.48-33.36% phenotypic variation explained (PVE) were identified using QTL Cartographer, while only 65 M-QTLs with 1.3-15.01% PVE were identified using QTLNetwork. A total of 53 M-QTLs were such which were identified using both programmes. On the other hand, GMM identified 186 (8.54-44.72% PVE) and 63 (7.11-21.13% PVE), three and two loci interactions, whereas only 8 E-QTL interactions with 1.7-8.34% PVE were identified through QTLNetwork. Interestingly a number of co-localized QTLs controlling 2-9 traits were also identified. The identification of few major, many minor M-QTLs and QTL × QTL interactions during the present study confirmed the complex and quantitative nature of drought tolerance in groundnut. This study suggests deployment of modern approaches like marker-assisted recurrent selection or genomic selection instead of marker-assisted backcrossing approach for breeding for drought tolerance in groundnut.
authors.affiliation: International Crops Research Institute for the Semi-Arid Tropics, Patancheru, India.
authors.forename: K
authors.initials: K
authors.lastname: Ravi
authors.forename: V
authors.initials: V
authors.lastname: Vadez
authors.forename: S
authors.initials: S
authors.lastname: Isobe
authors.forename: R R
authors.initials: RR
authors.lastname: Mir
authors.forename: Y
authors.initials: Y
authors.lastname: Guo
authors.forename: S N
authors.initials: SN
authors.lastname: Nigam
authors.forename: M V C
authors.initials: MV
authors.lastname: Gowda
authors.forename: T
authors.initials: T
authors.lastname: Radhakrishnan
authors.forename: D J
authors.initials: DJ
authors.lastname: Bertioli
authors.forename: S J
authors.initials: SJ
authors.lastname: Knapp
authors.forename: R K
authors.initials: RK
authors.lastname: Varshney
mesh_terms: D000222:Adaptation, Physiological / Q000235:genetics*; D010367:Arachis / Q000235:genetics*; D001947:Breeding; D002874:Chromosome Mapping; D032461:Chromosomes, Plant; D055864:Droughts; D004843:Epistasis, Genetic; D008040:Genetic Linkage; D005819:Genetic Markers; D005838:Genotype; D010641:Phenotype; D011110:Polymorphism, Genetic; D040641:Quantitative Trait Loci; D012984:Software
chemical_list: D005819:Genetic Markers