Genomic architecture of phenotypic plasticity of complex traits in tetraploid wheat in response to water stress

Abstract

Phenotypic plasticity is one of the main mechanisms of adaptation to abiotic stresses via changes in critical developmental stages. Altering flowering phenology is a key evolutionary strategy of plant adaptation to abiotic stresses in order to achieve maximum possible reproduction. The current study is the first to apply the linear regression residuals as a drought plasticity scores, while taking into account the differences in flowering phenology and trait variation under non-stress conditions. We characterized the genomic architecture of 17 complex traits and their drought plasticity using a mapping population derived from a cross between durum wheat (Triticum durum) and wild emmer wheat (T. dicoccoides). We identified 79 QTLs, of which 33 were plastic in response to water stress and exhibited epistatic interactions and/or pleiotropy between the initial and plasticity traits. Vrn-B3 (TaTF1) residing within an interval of a major drought-escape QTL was proposed as a candidate gene. The favorable alleles for most of the plasticity QTLs were contributed by wild emmer, demonstrating the high potential of wild relatives for wheat improvement. Our study presents a new approach for quantification of plant adaptation to various stresses and provides new insights into the genetic basis of wheat complex traits under water-deficit stress.HighlightThe study presents a new approach for quantification of plant adaptation to various stresses and provides new insights into the genetic basis of wheat complex traits under water-deficit stress.

Variation in phosphorus and sulfur content shapes the genetic architecture and phenotypic associations within wheat grain ionome

“…The RIL L×G population derived from a cross between durum wheat ( T. durum , cv. LDN) and WEW (accession G18-16) has been described previously (Peleg et al , 2009b; Fatiukha et al , 2019)). The population (150 F 6 RILs) was grown under three environments across two growing winter seasons (2004–2005 and 2006–2007) in an insect-proof screen-house at the experimental farm of the Hebrew University of Jerusalem in Rehovot, Israel.…”

“…Single nucleotide polymorphism (SNP) genotyping of 150 F 7 lines was performed using the Illumina Infinium 15K Wheat platform, developed by TraitGenetics, Gatersleben, Germany (Muqaddasi et al , 2017), consisting of 12,905 SNPs selected from the wheat 90K array (Wang et al , 2014). The genetic map contained 4,015 SNPs that represent 1,369 unique loci (skeleton markers) and covered 1835.7 cM (for more details see Fatiukha et al , 2019).…”

“…Concentrations of N in the samples were determined using C/N analyzer (TruSpec CN, Leco Co., USA), while grain protein concentration (GPC) was calculated by multiplying N percentage with conversion factor of 5.83 (Merrill & Watt, 1973). Phenotypes of 17 complex traits: grain yield (GY), thousand kernel weight (TKW), kernel number per spike (KNSP), harvest index (HI), spike dry matter (SpDM), total dry matter (TotDM), carbon isotope ratio (δ13C), osmotic potential (OP), chlorophyll content (Chl), flag leaf rolling (LR), culm length (CL), days from planting to heading (DP-H), days from heading to maturity (DH-M), vegetative dry matter (VegDM), spike length (SpL), flag leaf length (FLL), and flag leaf width (FLW) were collected in the first year of the experiment, as described in Peleg et al , (2009b) and Fatiukha et al , (2019).…”

“…The annotated gene models of ‘Zavitan’ genome assembly (Avni et al , 2017) were used to generate a list of genes residing within each QTL interval (1.5 LOD support interval of QTL effect with the highest LOD score), based on the physical positions of SNP markers that were previously assigned by Fatiukha et al , (2019). Potential candidate genes were selected from this list using functional annotations associated with ‘transport’ and ‘metabolism’ of ions and elements.…”

“…We previously evaluated WEW genotypes for grain mineral concentrations (Gomez-Becerra et al , 2010a) and identified QTLs affecting grain mineral content in a RIL population derived from a cross between durum wheat Langdon (hereafter LDN) and WEW accession G18-16 (L×G) using an old marker systems of SSRs and DArTs (Peleg et al , 2009a). Recent SNP genotyping of L×G RILs allowed us to improve the quality of the genetic map with over four-fold higher amount of skeletal (framework) markers (1,369 vs. 307 in previous map) and five-fold smaller average interval length between adjacent markers (1.3 cM vs.7.5 cM) (Fatiukha et al , 2019).…”