Meta‐Analysis of Wheat QTL Regions Associated with Adaptation to Drought and Heat Stress

Abstract

Drought and heat are the two most important environmental constraints to wheat (Triticum aestivum L.) production globally and are predicted to become more severe with global climate change. A number of recent studies have reported quantitative trait loci (QTL) for yield and agronomic traits in drought and heat‐stressed environments and for physiological traits that contribute to improved performance under stress. The objective of this study was to perform a meta‐analysis of reported QTL to identify meta‐QTL (MQTL) associated with adaptation to drought and heat stress. In the studies analyzed, QTL were reported for 81 different traits across a range of environments including both field and controlled experiments. A total of 854 individual QTL were reported, with 502 associated with drought stress, 234 with heat stress, and 118 with physiological traits in nonstressed environments. Individual QTL clustered into 66 MQTL regions distributed throughout the genome. There were 43 MQTL that co‐localized for both drought and heat stress, 20 specific for drought stress, 2 specific for heat stress, and 1 MQTL specific for physiological traits in nonstressed environments. Quantitative trait loci for plant height, days to maturity, kernel weight, spike density, and canopy temperature were most significantly associated with QTL for yield. Integration of 137 single nucleotide polymorphism (SNP) markers for heat‐ and drought‐responsive candidate genes identified 50 SNPs within MQTL confidence intervals, including genes involved in sugar metabolism, scavenging of reactive oxygen species, and abscisic‐acid‐induced stomatal closure. Identified MQTL and candidate genes can be targeted for future studies and genetic improvement of abiotic stress tolerance in wheat.

QTL Analysis for Drought Tolerance in Wheat: Present Status and Future Possibilities

“…Two of these QTLs were co-localized with MQTLs for drought/heat stress reported earlier [44]; (for MQTLs, see later). The importance of these QTLs is discussed in the following text for different classes of traits.…”

“…One QTL each were located on chromosomes 3B [45] and 7A [47,54]. The QTLs on chromosomes 4A and 7A also coincided with the MQTLs for drought/heat stress [44] and were mapped in genomic regions, which also harbor more than one QTL for one or more of the following traits: (i) days to heading; (ii) days to maturity; (iii) stay green habit; (iv) biomass; (v) CT; (vi) CID; (vii) coleoptile vigor; (viii) grain filling; (ix) plant height; (x) kernel number; (xi) spike density; (xii) 1000-kernal weight; (xiii) WSC; and (xiv) grain yield. These traits represent a spectrum of morphological and physiological traits contributing to seedling emergence, grain yield, and adaption to drought environments.…”

Detection of consensus genomic regions associated with root architecture of bread wheat on groups 2 and 3 chromosomes using QTL meta–analysis

“…This approach has been used to study different quantitative traits in various cereals such as abiotic stresses tolerance in barley , yield in rice (Wu et al, 2016), and disease resistance in maize . Meta-analysis of QTLs has been also employed for root architecture in rice , Brassica napus and adaptation to drought and heat stress in bread wheat (Acuña-Galindo et al, 2014). Despite of different studies, research is limited in using meta-analyses for studying root system morphology in wheat.…”

Quantifying Wheat Sensitivities to Environmental Constraints to Dissect Genotype × Environment Interactions in the Field

“…Therefore, yield and its components are highly dependent on genotypeby-environment (G 3 E) interactions (Tardieu, 2012;Addison et al, 2016). The associated quantitative trait loci (QTLs) also are highly dependent on temperature and water scenarios (Kuchel et al, 2007;Pinto et al, 2010;Acuna-Galindo et al, 2015;Millet et al, 2016).…”

“…Despite important progress in genetics, QTL-by-environment (QTL 3 E) interactions are most often analyzed in a qualitative way with significant or nonsignificant interactions across qualitative environments (El-Soda et al, 2015). This was the case in studies where wheat (Triticum aestivum) was grown under heat and/or drought conditions (Mathews et al, 2008;Pinto et al, 2010;Graziani et al, 2014;Acuna-Galindo et al, 2015;Addison et al, 2016).…”