Detection of grain yield QTLs in the durum population Lahn/Cham1 tested in contrasting environments

Durum wheat (Triticum turgidum L. var durum) is tetraploid wheat (AABB); it is the main source of semolina and other pasta products. Grain yield in wheat is quantitatively inherited and influenced by the environment. The genetic map construction constitutes the essential step in identifying quantitative trait loci (QTLs) linked to complex traits, such as grain yield. The study aimed to construct a genetic linkage map of two parents that are widely grown durum cultivars (Lahn and Cham1) in the Mediterranean basin, which is characterized by varying climate changes. The genetic linkage map of Lahn/Cham1 population consisted of 112 recombinant inbred lines (RILs) and was used to determine QTLs linked to the grain yield in 11 contrasting environments (favorable, cold, dry, and hot). Simple sequence repeat (SSR) molecular markers were used to construct an anchor map, which was later enriched with single nucleotide polymorphisms (SNPs). The map was constructed with 247 SSRs and enriched with 1425 SNPs. The map covered 6122.22 cM. One hundred and twenty-six QTLs were detected on different chromosomes. Chromosomes 2A and 4B harbored the most significant grain yield QTLs. Furthermore, by comparison with several wheat mapping populations, all the A and B chromosomes of Lahn/Cham1 QTLs contributed to grain yield. The results showed that the detected QTLs can be used as a potential candidate for marker-assisted selection in durum breeding programs.

Combining QTL Analysis and Genomic Predictions for Four Durum Wheat Populations Under Drought Conditions

Durum wheat is an important crop for the human diet and its consumption is gaining popularity. In order to ensure that durum wheat production maintains the pace with the increase in demand, it is necessary to raise productivity by approximately 1.5% per year. To deliver this level of annual genetic gain the incorporation of molecular strategies has been proposed as a key solution. Here, four RILs populations were used to conduct QTL discovery for grain yield (GY) and 1,000 kernel weight (TKW). A total of 576 individuals were sown at three locations in Morocco and one in Lebanon. These individuals were genotyped by sequencing with 3,202 high-confidence polymorphic markers, to derive a consensus genetic map of 2,705.7 cM, which was used to impute any missing data. Six QTLs were found to be associated with GY and independent from flowering time on chromosomes 2B, 4A, 5B, 7A and 7B, explaining a phenotypic variation (PV) ranging from 4.3 to 13.4%. The same populations were used to train genomic prediction models incorporating the relationship matrix, the genotype by environment interaction, and marker by environment interaction, to reveal significant advantages for models incorporating the marker effect. Using training populations (TP) in full sibs relationships with the validation population (VP) was shown to be the only effective strategy, with accuracies reaching 0.35–0.47 for GY. Reducing the number of markers to 10% of the whole set, and the TP size to 20% resulted in non-significant changes in accuracies. The QTLs identified were also incorporated in the models as fixed effects, showing significant accuracy gain for all four populations. Our results confirm that the prediction accuracy depends considerably on the relatedness between TP and VP, but not on the number of markers and size of TP used. Furthermore, feeding the model with information on markers associated with QTLs increased the overall accuracy.

Systems responses to progressive water stress in durum wheat

Durum wheat is susceptible to terminal drought which can greatly decrease grain yield. Breeding to improve crop yield is hampered by inadequate knowledge of how the physiological and metabolic changes caused by drought are related to gene expression. To gain better insight into mechanisms defining resistance to water stress we studied the physiological and transcriptome responses of three durum breeding lines varying for yield stability under drought. Parents of a mapping population (Lahn x Cham1) and a recombinant inbred line (RIL2219) showed lowered flag leaf relative water content, water potential and photosynthesis when subjected to controlled water stress time transient experiments over a six-day period. RIL2219 lost less water and showed constitutively higher stomatal conductance, photosynthesis, transpiration, abscisic acid content and enhanced osmotic adjustment at equivalent leaf water compared to parents, thus defining a physiological strategy for high yield stability under water stress. Parallel analysis of the flag leaf transcriptome under stress uncovered global trends of early changes in regulatory pathways, reconfiguration of primary and secondary metabolism and lowered expression of transcripts in photosynthesis in all three lines. Differences in the number of genes, magnitude and profile of their expression response were also established amongst the lines with a high number belonging to regulatory pathways. In addition, we documented a large number of genes showing constitutive differences in leaf transcript expression between the genotypes at control non-stress conditions. Principal Coordinates Analysis uncovered a high level of structure in the transcriptome response to water stress in each wheat line suggesting genome-wide co-ordination of transcription. Utilising a systems-based approach of analysing the integrated wheat’s response to water stress, in terms of biological robustness theory, the findings suggest that each durum line transcriptome responded to water stress in a genome-specific manner which contributes to an overall different strategy of resistance to water stress.

Genetic mapping of the gene affecting polyphenol oxidase activity in tetraploid durum wheat

The quality of durum wheat (Triticum turgidum ssp. durum) is influenced by polyphenol oxidase(PPO) activity and its corresponding substrates. A saturated molecular-marker linkage map was constructed previously by using a set of recombinant inbred (RI) lines, derived from a cross between durum wheat cultivars Jennah Khetifa and Cham 1. Quantitative trait loci (QTL) for PPO activity in seeds were mapped in this population. PPO activity in seeds of the parents and 110 RI lines was measured spectrophotometrically. The PPO activity of Cham 1 was significantly lower than that of Jennah Khetifa. QTL analysis of these data indicated that most of PPO activity was associated with major loci on the long arm of chromosome 2A. The trait was found to be strongly associated with the SSR marker Xgwm312@2A. With this knowledge, marker-assisted selection can be used to select genotypes with lower PPO activity in durum wheat populations.

A genetic linkage map of the Durum x Triticum dicoccoides backcross population based on SSRs and AFLP markers, and QTL analysis for milling traits

Durum wheat ( Triticum turgidum L. var durum) is mainly produced and consumed in the Mediterranean region; it is used to produce several specific end-products; such as local pasta, couscous and burghul. To study the genetics of grain-milling quality traits, chromosomal locations, and interaction with the environment, a genetic linkage map of durum was constructed and the quantitative trait loci QTLs for the milling-related traits, test weight (TW) and thousand-kernel weight (TKW), were identified. The population constituted 114 recombinant inbred lines derived from the cross: Omrabi 5 /Triticum dicoccoides 600545// Omrabi 5. TW and TKW were analyzed over 18 environments (sites x years). Single-sequence-repeat markers (SSRs), Amplified-fragment-length-polymorphism markers (AFLPs), and seed storage proteins (SSPs) showed a high level of polymorphism (>60%). The map was constructed with 124 SSRs, 149 AFLPs and 6 SSPs; its length covered 2,288.8 cM (8.2 cM/marker). The map showed high synteny with previous wheat maps, and both SSRs and AFLPs mapped evenly across the genome, with more markers in the B genome. However, some rearrangements were observed. For TW, a high genotypic effect was detected and two QTLs with epistasic effect were identified on 7AS and 6BS, explaining 30% of the total variation. The TKW showed a significant transgressive inheritance and five QTLs were identified, explaining 32% of the total variation, out of which 25% was of a genetic nature, and showing QTLxE interaction. The major TKW-QTLs were around the centromere region of 6B. For both traits, Omrabi 5 alleles had a significant positive effect. This population will be used to determine other QTLs of interest, as its parents are likely to harbor different genes for diseases and drought tolerance.

Identification of a microsatellite on chromosome 7B showing a strong linkage with yellow pigment in durum wheat (Triticum turgidum L. var. durum)

The objective of this study is to identify QTLs linked to yellow pigment content in durum wheat. A durum-dicoccoides genetic linkage map was constructed using 124 microsatellites, 149 amplified fragment length polymorphism (AFLPs), and six seed storage proteins (SSP) in a population of 114 recombinant inbred lines (F8). The population has been obtained from a cross between a durum cultivar Omrabi5 and Triticum dicoccoides600545 and backcrossed to Omrabi5. The map consists of 14-durum chromosomes plus an unknown group; and shows a good synteny to the previously published wheat maps. Yellow pigment was measured in the population in three different locations during 3 seasons. Analysis of QTLs was based on simple and simplified composite interval mapping (SIM and sCIM). Three QTLs for yellow pigment were detected on the chromosomal group 7 (7AL and 7BL telomeres) explaining 62% of the total variation. On 7BL, a major microsatellite (Xgwm344) explained by itself 53%, whereas on 7AL, the other two QTLs have contributed 13 and 6%. All determined QTLs showed a strong genetic effect and a weak QTL x E effect. The QTLs effect was consistent across all environments and showed a large effect. Consequently, promising QTLs will be used in the marker assisted breeding program to enhance the selection efficiency for yellow pigment.

Genetic variation among populations of the Hessian fly Mayetiola destructor (Diptera: Cecidomyiidae) in Morocco and Syria

The RAPD-PCR technique was used to study genetic variation within and among geographical populations of the Hessian fly, Mayetiola destructor (Say), from Morocco and Syria, associated with the fly's ability to overcome resistance in three wheat cultivars containing H5, H13 and H22 resistance genes. Variation was detected both for the level of susceptibility of the cultivars and RAPD profiles of M. destructor populations. By the use of RAPD-PCR, high genetic variability was detected among individuals and populations of M. destructor within and between areas separated geographically. The DNA fingerprints of populations of M. destructor were area-specific with Nei's measures of genetic distance ranging from 0.156 (between Abda and Beni Mellal, Morocco) to 1.977 (between Marchouch, Morocco and Lattakia, Syria). Cluster analysis of the genetic distances among the populations, identified the Syrian population as an outlier. A highly significant correlation (r = 0.81) observed between the genetic and geographic distances among the populations, provided genetic support for dispersal of the fly from its presumed origin in West Asia to Morocco.

Use of AMMI and linear regression models to analyze genotype-environment interaction in durum wheat

The joint durum wheat (Triticum turgidum L var 'durum') breeding program of the International Maize and Wheat Improvement Center (CIMMYT) and the International Center for Agricultural Research in the Dry Areas (ICARDA) for the Mediterranean region employs extensive multilocation testing. Multilocation testing produces significant genotype-environment (GE) interaction that reduces the accuracy for estimating yield and selecting appropriate germ plasm. The sum of squares (SS) of GE interaction was partitioned by linear regression techniques into joint, genotypic, and environmental regressions, and by Additive Main effects and the Multiplicative Interactions (AMMI) model into five significant Interaction Principal Component Axes (IPCA). The AMMI model was more effective in partitioning the interaction SS than the linear regression technique. The SS contained in the AMMI model was 6 times higher than the SS for all three regressions. Postdictive assessment recommended the use of the first five IPCA axes, while predictive assessment AMMI1 (main effects plus IPCA1). After elimination of random variation, AMMI1 estimates for genotypic yields within sites were more precise than unadjusted means. This increased precision was equivalent to increasing the number of replications by a factor of 3.7.