Dissection of the genetic basis of genotype-by-environment interactions for grain yield and main agronomic traits in Iranian bread wheat landraces and cultivars

Understanding the genetic basis of performance stability is essential to maintain productivity, especially under severe conditions. In the present study, 268 Iranian bread wheat landraces and cultivars were evaluated in four well-watered and two rain-fed conditions for different traits. According to breeding programs, cultivars were in a group with a high mean and stability in terms of GY, GN, and SW traits, while in terms of PH, they had a low mean and high stability. The stability of cultivars and landraces was related to dynamic and static stability, respectively. The highest number of marker pairs and lowest LD decay distance in both cultivars and landraces was observed on the B genome. Population structure differentiated indigenous cultivars and landraces, and the GWAS results for each were almost different despite the commonalities. Chromosomes 1B, 3B, 7B, 2A, and 4A had markers with pleiotropic effects on the stability of different traits. Due to two rain-fed environments, the Gene Ontology (GO) confirmed the accuracy of the results. The identified markers in this study can be helpful in breeding high-performance and stable genotypes and future breeding programs such as fine mapping and cloning

Genome-Wide Association Study (GWAS) and genome prediction of seedling salt tolerance in bread wheat (Triticum aestivum L.)

Background: Salinity tolerance in wheat is imperative for improving crop genetic capacity in response to the expanding phenomenon of soil salinization. However, little is known about the genetic foundation underlying salinity tolerance at the seedling growth stage of wheat. Herein, a GWAS analysis was carried out by the random-SNP-effect mixed linear model (mrMLM) multi-locus model to uncover candidate genes responsible for salt tolerance at the seedling stage in 298 Iranian bread wheat accessions, including 208 landraces and 90 cultivars.Results: A total of 29 functional marker-trait associations (MTAs) were detected under salinity, 100 mM NaCl (sodium chloride). Of these, seven single nucleotide polymorphisms (SNPs) including rs54146, rs257, rs37983, rs18682, rs55629, rs15183, and rs63185 with R-2 >= 10% were found to be linked with relative water content, root fresh weight, root dry weight, root volume, shoot high, proline, and shoot potassium (K+), respectively. Further, a total of 27 candidate genes were functionally annotated to be involved in response to the saline environment. Most of these genes have key roles in photosynthesis, response to abscisic acid, cell redox homeostasis, sucrose and carbohydrate metabolism, ubiquitination, transmembrane transport, chromatin silencing, and some genes harbored unknown functions that all together may respond to salinity as a complex network. For genomic prediction (GP), the genomic best linear unbiased prediction (GBLUP) model reflected genetic effects better than both bayesian ridge regression (BRR) and ridge regression-best linear unbiased prediction (RRBLUP), suggesting GBLUP as a favorable tool for wheat genomic selection.Conclusion: The SNPs and candidate genes identified in the current work can be used potentially for developing salt-tolerant varieties at the seedling growth stage by marker-assisted selection

Relationship between Pigments and Seed Fall Rate of Iranian Castor Genotypes and Genetic Diversity

This study aimed to examine the relationship between pigments and seed fall rate of Iranian castor genotypes and genetic diversity, specifically 28 castor genotypes (27 native and 1 modified), a randomized complete block design with three replications was conducted in 2014 and 2015 at the Research Farm of Islamic Azad University in Damghan, northern Iran. During the growth period, the following traits were sampled: seed length; seed width; weight of 1,000 seeds; color of seed coat; number of leaves in the bush; leaf, nervure, and stem color; seed fall rate; growth type; seed performance; oil percentage; and chlorophyll fluorescence rate. After data collection, variance analysis was conducted through SAS and mean comparison was performed through Duncan test at 5% probability level. Correlation coefficients were calculated to find correlations, and cluster analysis was used to group the genotypes. Finally, graphs were drawn with Excel. The results indicated diversity in the investigated traits. Differences were observed among the native castor genotypes so that they were divided into five groups in terms of grain fall rate. A significant negative correlation at 1% probability level between the grain fall rate and the leaf color (r= –0.71**), nervure color (r= –0.56**), and stem color (r= –0.57**) indicated that in all of these three traits, when the color changed to dark red, the rate of grain loss decreased. Thus, the color trait can be used as a reference in breeding programs so that grain fall in the castor plant can be prevented in the future

Characterization of Dynamic Regulatory Gene and Protein Networks in Wheat Roots Upon Perceiving Water Deficit Through Comparative Transcriptomics Survey

A well-developed root system benefits host plants by optimizing water absorption and nutrient uptake and thereby increases plant productivity. In this study we have characterized the root transcriptome using RNA-seq and subsequential functional analysis in a set of drought tolerant and susceptible genotypes. The goal of the study was to elucidate and characterize water deficit-responsive genes in wheat landraces that had been through long-term field and biochemical screening for drought tolerance. The results confirm genotype differences in water-deficit tolerance in line with earlier results from field trials. The transcriptomics survey highlighted a total of 14,187 differentially expressed genes (DEGs) that responded to water deficit. The characterization of these genes shows that all chromosomes contribute to water-deficit tolerance, but to different degrees, and the B genome showed higher involvement than the A and D genomes. The DEGs were mainly mapped to flavonoid, phenylpropanoid, and diterpenoid biosynthesis pathways, as well as glutathione metabolism and hormone signaling. Furthermore, extracellular region, apoplast, cell periphery, and external encapsulating structure were the main water deficit-responsive cellular components in roots. A total of 1,377 DEGs were also predicted to function as transcription factors (TFs) from different families regulating downstream cascades. TFs from the AP2/ERF-ERF, MYB-related, B3, WRKY, Tify, and NAC families were the main genotype-specific regulatory factors. To further characterize the dynamic biosynthetic pathways, protein-protein interaction (PPI) networks were constructed using significant KEGG proteins and putative TFs. In PPIs, enzymes from the CYP450, TaABA8OH2, PAL, and GST families play important roles in water-deficit tolerance in connection with MYB13-1, MADS-box, and NAC transcription factors

Marker-Assisted Selection for Recognizing Wheat Mutant Genotypes Carrying HMW Glutenin Alleles Related to Baking Quality

Allelic diversity of HMW glutenin loci in several studies revealed that allelic combinations affect dough quality. Dx5 + Dy10 subunits are related to good baking quality and Dx2 + Dy12 are related to undesirable baking quality. One of the most regular methods to evaluate the baking quality is SDS-PAGE which is used to improve baking quality labs. Marker-assisted selection is the method which can recognize the alleles related to baking quality and this method is based on polymerase chain reaction. 10 pairs of specific primers related to Dx2, Dx2.1, Dx5, Dy10, and Dy12 subunits were used for recognizing baking quality of some wheat varieties and some mutant genotypes. Only 5 pairs of them could show the specific bands. All subunits were recognized by the primers except Dx2.1. Some of the primers were extracted from previous studies and the others were designed based on D genome subunits of wheat. SDS-PAGE method accomplished having confidence in these marker’s results. To realize the effect of mutation, seed storage proteins were measured. It showed that mutation had effect on the amount of seed storage protein on the mutant seeds (which showed polymorphism)

Development of IRAP- and REMAP-derived SCAR markers for marker-assisted selection of the strip rust resistance gene Yr15 derived from wild emmer wheat

Stripe rust (Pucinia striformis f.sp. tritici) is one of the most important fungal diseases of wheat, found on all continents and in over 60 countries. Wild emmer wheat, Triticum dicoccoides, which is the tetraploid progenitor of durum wheat, is a valuable source of novel stripe rust resistance genes for wheat breeding. T. dicoccoides G25 accession carries Yr15, a gene on chromosome arm 1BS. Yr15 confers resistance to all known stripe rust isolates; it is also effective in introgressed durum and bread wheat. Retrotransposons generate polymorphic insertions, which can be scored as Mendelian markers with techniques including REMAP and IRAP. Six REMAP and IRAP-derived SCAR markers were developed using 1256 F2 plants derived from crosses of the susceptible T. durum accession D447 with its resistant BC3F9 and BC3F10 (B9 and B10) near isogenic lines, which carried Yr15 introgressed from G25. The nearest markers segregated 0.1 cM proximally and 1.1 cM distally to Yr15. These markers were also mapped and validated at the same position in another independent 500 F2 plants derived from crosses of B9 and B10 with the susceptible cultivar Langdon. SCAR270 and SCAR790, surrounding Yr15 at an interval of 1.2 cM, were found to be reliable and robust co-dominant markers in a wide range of wheat lines and cultivars with and without Yr15. These markers are useful tags in marker-assisted wheat breeding programs aiming to incorporate Yr15 into elite wheat lines and cultivars for durable and broad-spectrum resistance against stripe rust.Peer reviewe

Differential responses of wheat genotypes to irrigation regimes through antioxidant defense system, grain yield, gene expression, and grain fatty acid profile

Wheat production under water-limited conditions is lagging due to our restricted understanding of mechanisms involved in drought tolerance. This study was aimed at the assessment of molecular and physio-biochemical responses of three wheat genotypes including Baran (drought-tolerant), Pishtaz (semi-tolerant) and Zarrin (sensitive). The plants were normally irrigated until the four-leaf stage, and then the irrigation was stopped until the soil moisture reached the desired stress at 100% (normal), 70%, and 40% soil field capacity (FC). The results revealed that leaf total protein content decreased under stress, while proline, catalase (CAT), ascorbate peroxidase (APX), and guaiacol peroxidase (GPX) increased. Drought stress at 40% FC decreased grain yield by 18, 20, and 39% for Barran, Pishtaz, and Zarrin, respectively. The gene expression of CAT, APX, GPX, pyrroline-5-carboxylate synthase (P5CS), and Pyrroline-5-carboxylate reductase (P5CR) significantly increased at drought, and tolerant genotype represented the higher rate of the gene expression compared with other genotypes. The proline level positively and strongly correlated with P5CS and P5CR gene expression. Grain fatty acid profile showed increased polyunsaturated fatty acid and decreased saturated fatty acids in plants experiencing 40% FC over control. Heat map analysis showed that CAT, APX, GPX, and proline with higher variability can be determined as markers to measure drought impacts. Overall, our findings represented the superior genotype for wheat breeding and also showed the physiological and biochemical changes particularly grain fatty acid profile to obtain the better genotype and irrigation regime in terms of human health

Relationship between allelic variation at the Glu-3 loci and qualitative traits in bread wheat

Low molecular weight glutenin subunits (LMW-GS), significantly influence the end-use quality of flour. In this study, a total of 63 Iranian bread wheat were used to evaluate allelic variation at loci encoding LMW-GS using SDS-PAGE and their gene-specific PCR primers, and allele-trait association analysis. Eight types of alleles were detected at the Glu-A3 locus by two primer pairs, in which Glu-A3c (31%) had the most frequent allele. Three specific primers detected 17 alleles at Glu-B3 locus, the high frequency of which belongs to Glu-B3f with 14.5%. For Glu-D3 locus; in total, 22 alleles were identified by four specific primers and Glu-D3h allele was the most frequent. 5, 9 and 9 alleles were identified by SDS-PAGE technique at the Glu-A3, Glu-B3 and Glu-D3 loci, respectively, the most frequent of which belongs to Glu-A3c with 40%. Using Nei’s genetic variation index (H), the allelic variation for Glu-A3, Glu-B3 and Glu-D3 loci, were estimated as 0.818, 0.914, and 0.910, respectively. The mean allelic variation (H) for Glu-3 loci was 0.894 among the genotypes. The results of allele-trait associations demonstrated that Glu-A3a and Glu-A3e were associated with high volume of SDS-sediment. The Glu-B3b, Glu-B3f, Glu-B3d and Glu-B3a were associated with high protein content, wet and dry gluten, and bread volume as well as hectoliter weight. Moreover, Glu-D3r was correlated to kernel hardness. The identified allelic variation and associated alleles with quality traits provided helpful information for marker-assisted breeding programs to improve bread-making quality