A dataset on multi-trait selection approaches for screening desirable wild relatives of wheat

Wild relatives of common wheat are an extraordinary source of tolerance to various environmental stresses. The dataset herein presents the effect of water-deficit stress on a core collection of landraces and wild relatives of wheat (including 180 samples belonging to four Triticum and eight Aegilops species [T. boeoticum Bioss., T. urartu Gandilyan., T. durum Def., T. aestivum L., Ae. speltoides Tausch., Ae. tauschii Coss., Ae. caudata L., Ae. umbellulata Zhuk., Ae. neglecta L., Ae. cylindrica Host., Ae. crassa Boiss., and Ae. triuncialis]) in terms of several physiological traits, root and shoot biomasses, and features of root system architecture (RSA). All genetic materials were subjected to water-stress treatment using a pot experiment under greenhouse conditions. To screen the most tolerant accessions, three selection indices, such as Smith and Hazel (SH), factor analysis and ideotype‐design (FAI), and the multi-trait genotype-ideotype distance index (MGIDI) were computed. The obtained data can highlight the role of some features of RSA in increasing water-deficit tolerance in some wild relatives of wheat. Moreover, the use of selection indices in the early stage of growth can be highlighted for future research.Peer reviewe

Dataset on the use of MGIDI index in screening drought-tolerant wild wheat accessions at the early growth stage

The dataset herein indicated the novelty of the article entitled “Dataset on the use of MGIDI in screening drought-tolerant wild wheat accessions at the early growth stage”. Data were gathered during 2018-2019 on a set of wild wheat germplasm under two control and water deficit stress conditions. One hundred and forty-six accessions belonging to Ae. tauschii, Ae. cylindrica, and Ae. crassa were assessed under optimal glasshouse conditions to screen the drought-tolerant samples at the early growth stage. Nine drought tolerance and susceptibility indices along with the multi-trait genotype-ideotype distance index (MGIDI) were used to visualize the dataset. The obtained data can highlight the potential of the MGIDI index in accelerating screening of a large number of plant materials using multiple traits or selection indices in crop breeding programs, especially at the early growth stage.Peer reviewe

Stability Indices to Deciphering the Genotype-by-Environment Interaction (GEI) Effect: An Applicable Review for Use in Plant Breeding Programs

Experiments measuring the interaction between genotypes and environments measure the spatial (e.g., locations) and temporal (e.g., years) separation and/or combination of these factors. The genotype-by-environment interaction (GEI) is very important in plant breeding programs. Over the past six decades, the propensity to model the GEI led to the development of several models and mathematical methods for deciphering GEI in multi-environmental trials (METs) called “stability analyses”. However, its size is hidden by the contribution of improved management in the yield increase, and for this reason comparisons of new with old varieties in a single experiment could reveal its real size. Due to the existence of inherent differences among proposed methods and analytical models, it is necessary for researchers that calculate stability indices, and ultimately select the superior genotypes, to dissect their usefulness. Thus, we have collected statistics, as well as models and their equations, to explore these methods further. This review introduces a complete set of parametric and non-parametric methods and models with a selection pattern based on each of them. Furthermore, we have aligned each method or statistic with a matched software, macro codes, and/or scripts

Effect of Methyl Jasmonate on Thymol, Carvacrol, Phytochemical Accumulation, and Expression of Key Genes Involved in Thymol/Carvacrol Biosynthetic Pathway in Some Iranian Thyme Species

Thyme species are a good source of thymol and carvacrol, which play a key role in controlling diseases. For the first time, the expression patterns of γ-terpinene synthase (TPS2), CYP71D178, and CYP71D180 genes and the amount of phenolics compounds were evaluated in T. migricus and T. daenensis after different methyl jasmonate (MeJA) treatments. The highest thymol and carvacrol contents were observed in T. migricus (86.27%) and T. daenensis (17.87%) at MeJA 100 µM, which was consistent with the expression patterns of the three investigated genes. All species treated showed high total phenolic and flavonoid content compared to control plants for which the highest amounts were observed in T. vulgaris treated with 100 µM and 10 µM MeJA. Furthermore, in the 100 µM MeJA treatment, the relative expression of TPS2 and CYP71D178 in T. migricus increased 7.47 and 9.86-fold compared with the control, respectively. The highest level of CYP71D180 transcripts (5.15-fold) was also observed for T. daenensis treated. This finding highlights the notion that thymol was known as the dominant component of the essential oil rather than carvacrol in diffident thyme species. This implies that MeJA at different concentrations influenced metabolic pathways and induced expression changes, resulting in a rise in essential oil levels

Stability Indices to Deciphering the Genotype-by-Environment Interaction (GEI) Effect: An Applicable Review for Use in Plant Breeding Programs

Experiments measuring the interaction between genotypes and environments measure the spatial (e.g., locations) and temporal (e.g., years) separation and/or combination of these factors. The genotype-by-environment interaction (GEI) is very important in plant breeding programs. Over the past six decades, the propensity to model the GEI led to the development of several models and mathematical methods for deciphering GEI in multi-environmental trials (METs) called “stability analyses”. However, its size is hidden by the contribution of improved management in the yield increase, and for this reason comparisons of new with old varieties in a single experiment could reveal its real size. Due to the existence of inherent differences among proposed methods and analytical models, it is necessary for researchers that calculate stability indices, and ultimately select the superior genotypes, to dissect their usefulness. Thus, we have collected statistics, as well as models and their equations, to explore these methods further. This review introduces a complete set of parametric and non-parametric methods and models with a selection pattern based on each of them. Furthermore, we have aligned each method or statistic with a matched software, macro codes, and/or scripts

Change in Secondary Metabolites and Expression Pattern of Key Rosmarinic Acid Related Genes in Iranian Lemon Balm (Melissa officinalis L.) Ecotypes Using Methyl Jasmonate Treatments

The medicinal herb, lemon balm (Melissa officinalis L.), which is high in rosmarinic acid (RA), has well-known therapeutic value. The goals of this study were to investigate the effects of methyl jasmonate (MeJA) on RA content, total phenolic content (TPC), and total flavonoid content (TFC), as well as changes in expression of their biosynthesis-related key genes (MoPAL, Mo4CL, and MoRAS) in Iranian lemon balm ecotypes, as first reported. Our results revealed that MeJA doses significantly increase the RA content, TPC, and TFC in both ecotypes compared with the control samples. Additionally, the higher expression levels of MoPAL, Mo4CL, and MoRAS following treatment were linked to RA accumulation in all treatments for both Iranian lemon balm ecotypes. After 24 h of exposure to 150 mu M MeJA concentration, HPLC analysis showed that MeJA significantly increased RA content in Esfahan and Ilam ecotypes, which was about 4.18- and 7.43-fold higher than untreated plants. Our findings suggested that MeJA has a considerable influence on RA, TPC, and TFC accumulation in MeJA-treated Iranian M. officinalis, which might be the result of gene activation from the phenylpropanoid pathway. As a result of our findings, we now have a better understanding of the molecular processes behind RA production in lemon balm plants.Peer reviewe

Change in Secondary Metabolites and Expression Pattern of Key Rosmarinic Acid Related Genes in Iranian Lemon Balm (Melissa officinalis L.) Ecotypes Using Methyl Jasmonate Treatments

The medicinal herb, lemon balm (Melissa officinalis L.), which is high in rosmarinic acid (RA), has well-known therapeutic value. The goals of this study were to investigate the effects of methyl jasmonate (MeJA) on RA content, total phenolic content (TPC), and total flavonoid content (TFC), as well as changes in expression of their biosynthesis-related key genes (MoPAL, Mo4CL, and MoRAS) in Iranian lemon balm ecotypes, as first reported. Our results revealed that MeJA doses significantly increase the RA content, TPC, and TFC in both ecotypes compared with the control samples. Additionally, the higher expression levels of MoPAL, Mo4CL, and MoRAS following treatment were linked to RA accumulation in all treatments for both Iranian lemon balm ecotypes. After 24 h of exposure to 150 µM MeJA concentration, HPLC analysis showed that MeJA significantly increased RA content in Esfahan and Ilam ecotypes, which was about 4.18- and 7.43-fold higher than untreated plants. Our findings suggested that MeJA has a considerable influence on RA, TPC, and TFC accumulation in MeJA-treated Iranian M. officinalis, which might be the result of gene activation from the phenylpropanoid pathway. As a result of our findings, we now have a better understanding of the molecular processes behind RA production in lemon balm plants

An Analysis of Genetic Variability and Population Structure in Wheat Germplasm Using Microsatellite and Gene-Based Markers

Knowledge of the natural patterns of genetic variation and their evolutionary basis is required for sustainable management and conservation of wheat germplasm. In the current study, the genetic diversity and population structure of 100 individuals from four Triticum and Aegilops species (including T. aestivum, Ae. tauschii, Ae. cylindrica, and Ae. crassa) were investigated using two gene-based markers (start codon targeted (SCoT) polymorphism and CAAT-box derived polymorphism (CBDP)) and simple-sequence repeats (SSRs). The SCoT, CBDP, and SSR markers yielded 76, 116, and 48 polymorphism fragments, respectively. The CBDP marker had greater efficiency than the SCoT and SSR markers due to its higher polymorphism content information (PIC), resolving power (Rp), and marker index (MI). Based on an analysis of molecular variance (AMOVA) performed using all marker systems and combined data, there was a higher distribution of genetic variation within species than among them. Ae. cylindrica and Ae. tauschii had the highest values for all genetic variation parameters. A cluster analysis using each marker system and combined data showed that the SSR marker had greater efficiency in grouping of tested accessions, such that the results of principal coordinate analysis (PCoA) and population structure confirmed the obtained clustering patterns. Hence, combining the SCoT and CBDP markers with polymorphic SSR markers may be useful in genetic fingerprinting and fine mapping and for association analysis in wheat and its germplasm for various agronomic traits or tolerance mechanisms to environmental stresses

An Analysis of Genetic Variability and Population Structure in Wheat Germplasm Using Microsatellite and Gene-Based Markers

Knowledge of the natural patterns of genetic variation and their evolutionary basis is required for sustainable management and conservation of wheat germplasm. In the current study, the genetic diversity and population structure of 100 individuals from four Triticum and Aegilops species (including T. aestivum, Ae. tauschii, Ae. cylindrica, and Ae. crassa) were investigated using two gene-based markers (start codon targeted (SCoT) polymorphism and CAAT-box derived polymorphism (CBDP)) and simple-sequence repeats (SSRs). The SCoT, CBDP, and SSR markers yielded 76, 116, and 48 polymorphism fragments, respectively. The CBDP marker had greater efficiency than the SCoT and SSR markers due to its higher polymorphism content information (PIC), resolving power (Rp), and marker index (MI). Based on an analysis of molecular variance (AMOVA) performed using all marker systems and combined data, there was a higher distribution of genetic variation within species than among them. Ae. cylindrica and Ae. tauschii had the highest values for all genetic variation parameters. A cluster analysis using each marker system and combined data showed that the SSR marker had greater efficiency in grouping of tested accessions, such that the results of principal coordinate analysis (PCoA) and population structure confirmed the obtained clustering patterns. Hence, combining the SCoT and CBDP markers with polymorphic SSR markers may be useful in genetic fingerprinting and fine mapping and for association analysis in wheat and its germplasm for various agronomic traits or tolerance mechanisms to environmental stresses