Wild relatives of wheat: Aegilops–Triticum accessions disclose differential antioxidative and physiological responses to water stress

Ahmadi, Jafar; Pour-Aboughadareh, Alireza; Ourang, Sedigheh Fabriki; Mehrabi, Ali Ashraf; Siddique, Kadambot H. M.

doi:10.1007/s11738-018-2673-0

Cited by 51 publications

(46 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Details on the growing conditions, stress treatments, and data collection are available in Ahmadi et al. (). The results of this data set are summarized in Appendix .…”

Section: Methods and Resultsmentioning

confidence: 99%

See 1 more Smart Citation

iPASTIC: An online toolkit to estimate plant abiotic stress indices

et al. 2019

Self Cite

View full text Add to dashboard Cite

Premise In crop breeding programs, breeders use yield performance in both optimal and stressful environments as a key indicator for screening the most tolerant genotypes. During the past four decades, several yield‐based indices have been suggested for evaluating stress tolerance in crops. Despite the well‐established use of these indices in agronomy and plant breeding, a user‐friendly software that would provide access to these methods is still lacking. Methods and Results The Plant Abiotic Stress Index Calculator ( i PASTIC ) is an online program based on JavaScript and R that calculates common stress tolerance and susceptibility indices for various crop traits including the tolerance index ( TOL ), relative stress index ( RSI ), mean productivity ( MP ), harmonic mean ( HM ), yield stability index ( YSI ), geometric mean productivity ( GMP ), stress susceptibility index ( SSI ), stress tolerance index ( STI ), and yield index ( YI ). Along with these indices, this easily accessible tool can also calculate their ranking patterns, estimate the relative frequency for each index, and create heat maps based on Pearsonʼs and Spearmanʼs rank‐order correlation analyses. In addition, it can also render three‐dimensional plots based on both yield performances and each index to separate entry genotypes into Fernandezʼs groups (A, B, C, and D), and perform principal component analysis. The accuracy of the results calculated from our software was tested using two different data sets obtained from previous experiments testing the salinity and drought stress in wheat genotypes, respectively. Conclusions i PASTIC can be widely used in agronomy and plant breeding programs as a user‐friendly interface for agronomists and breeders dealing with large volumes of data. The software is available at https://mohsenyousefian.com/ipastic/ .

show abstract

“…Details on the growing conditions, stress treatments, and data collection are available in Ahmadi et al. (). The results of this data set are summarized in Appendix .…”

Section: Methods and Resultsmentioning

confidence: 99%

“…The water stress treatment (FC = 25 ± 5%) was initiated at the three-leaf stage of growth. Details on the growing conditions, stress treatments, and data collection are available in Ahmadi et al (2018a). The results of this data set are summarized in Appendix S10.…”

Section: Testing Ipastic Softwarementioning

confidence: 99%

iPASTIC: An online toolkit to estimate plant abiotic stress indices

et al. 2019

Self Cite

View full text Add to dashboard Cite

show abstract

“…Hence, distribution of this germplasm in the different parts of Iran, suggest that this area is an ideal source of diversity for discovering useful genes to transfer into modern wheat. Several studies reported that T. urartu is an ideal source of genes related to seed quality, tolerance to both biotic [especially for leaf rust and powdery mildew diseases] and abiotic [especially for drought, salinity and cold] stresses tolerance [4][5][6][7][8][9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Assessment of genetic diversity inTriticum urartuThumanjan ex Gandilyan accessions using start codon targeted polymorphism (SCoT) and CAAT-box derived polymorphism (CBDP) markers

Gholamian

Etminan

Changizi

et al. 2019

Biotechnology & Biotechnological Equipment

View full text Add to dashboard Cite

show abstract

“…Within this review, we have compiled the information from the studies carried out in wheat using QTL mapping methodologies that is among the best methods for biofortification traits. We hope this review will serve as an essential reference for the QTLs identified for the several important biofortification traits in wheat.that could contribute to underexploited wild relatives [25,26]. The different steps involved in the development of biofortification wheat with the aid of marker-assisted breeding are presented in Figure1.…”

mentioning

confidence: 99%

“…that could contribute to underexploited wild relatives [25,26]. The different steps involved in the development of biofortification wheat with the aid of marker-assisted breeding are presented in Figure1.…”

mentioning

confidence: 99%

QTLs identified for Biofortification Traits in Wheat: A Review

Devi¹,

Kaushik²,

Saini³

2019

Preprint

View full text Add to dashboard Cite

Wheat is the essential constituent of cereal-based diets and one of the most significant sources of calories. However, there is an inherently low bioavailability of proteins, mineral, and vitamins in modern wheat grains. Biofortification has earned recognition as an outstanding approach, at the same time as a cure for world hunger. The developments in the identifications of quantitative trait loci (QTL) analysis and understanding of the physiological and molecular basis of QTLs controlling the biofortification traits in wheat has revealed new horizons for the improvement of modern wheat varieties. Within this review, we have compiled the information from the studies carried out in wheat using QTL mapping methodologies that is among the best methods for biofortification traits. We hope this review will serve as an essential reference for the QTLs identified for the several important biofortification traits in wheat.that could contribute to underexploited wild relatives [25,26]. The different steps involved in the development of biofortification wheat with the aid of marker-assisted breeding are presented in Figure1. Figure 1.Representation of different strategies for biofortification of the wheat, especially explaining different steps of marker-assisted breeding.Conventional breeding methods are easy to operate with qualitative traits. These traits depend on a single gene whereas traits like yield are quantitative and therefore are impacted by several genes [27,28,29]. There are several techniques for mapping quantitative trait loci (QTL) in an experimental cross [30]. The molecular basis of QTLs is challenging to dissect, even for model plants like Arabidopsis and rice, because of the problems in precisely narrowing intervals to single genes [31]. Experimental design, type of plant population analysed and the level of polymorphisms between parental genomes also affect the predictions of QTLs. Statistical methods to determine quantitative trait loci (QTL) require numerous molecular markers with high-resolution genetic maps [32,33]. This approach is also related to genomics methods which are geared toward the dissection of complex phenotypes [34].Genomic resources of wheat have provided important support for functional genomics and conservation biology (by conserving the important landraces) [35,36]. The wheat genome is complex to interpret simply because of broadly dispersed repetitive sequences, heterozygosity, and polyploidy [37,38]. Nevertheless, the developments in sequencing methodologies, decreased sequencing price, together with the advancements in the computational resources have permitted the spread of these resources [39,40]. Besides, the comparative genomics among plant species is demonstrating to be an efficient method for the identification of novel genes regarding the biofortification of modern wheat [41]. Therefore, in this review, we have compiled the QTLs Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted:

show abstract

Wild relatives of wheat: Aegilops–Triticum accessions disclose differential antioxidative and physiological responses to water stress

Cited by 51 publications

References 43 publications

iPASTIC: An online toolkit to estimate plant abiotic stress indices

iPASTIC: An online toolkit to estimate plant abiotic stress indices

Assessment of genetic diversity inTriticum urartuThumanjan ex Gandilyan accessions using start codon targeted polymorphism (SCoT) and CAAT-box derived polymorphism (CBDP) markers

QTLs identified for Biofortification Traits in Wheat: A Review

Contact Info

Product

Resources

About