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1.
Plant Physiol Biochem ; 196: 668-682, 2023 Mar.
Article in English | MEDLINE | ID: mdl-36801772

ABSTRACT

Biostimulants such as ascorbic acid (AA) and fulvic acid (FA)can enhance the efficiency of root-nodulating bacteria. This study investigates optimum concentration of these two biostimulants to maximize the Rhizobium activity and increase root size, nodulation capability, NPK uptake, yield and quality. Interaction with nitrogenase enzyme through molecular docking was also studied by using both AA and FA as ligands to better understand their inhibitory role in excess amounts. The findings of the study suggest: the combined application of both FA and AA at 200 ppm concentrations proved to be more effective than the individual application. Excellent vegetative growth was noticed which translated into an increased reproductive growth i.e statistically significant increase in number of pods per plant, fresh and dry weight of pods per plant, number of seeds per pod, total chlorophyll, carotenoids and chemical constituents of pea seeds i.e. N (16.17%), P (40.47%), K (39.96%) and protein (16.25%). These findings were substantiated by molecular docking of nitrogenase enzyme with ascorbic acid and fulvic acid. The XP docking score of ascorbic acid (-7.07 kcal mol-1) and fulvic acid (-6.908 kcal mol-1) exhibited that the optimum doses (200 ppm) should be used as higher dose or their excess amount can hinder the Rhizobium activity of nitrogen fixation by interacting with the nitrogenase enzyme.


Subject(s)
Meteoroids , Rhizobium , Pisum sativum/metabolism , Ascorbic Acid/pharmacology , Molecular Docking Simulation , Nitrogenase/metabolism
2.
Theor Appl Genet ; 134(11): 3699-3719, 2021 Nov.
Article in English | MEDLINE | ID: mdl-34333664

ABSTRACT

KEY MESSAGE: Using phenotypic data of four biparental spring wheat populations evaluated at multiple environments under two management systems, we discovered 152 QTL and 22 QTL hotspots, of which two QTL accounted for up to 37% and 58% of the phenotypic variance, consistently detected in all environments, and fell within genomic regions harboring known genes. Identification of the physical positions of quantitative trait loci (QTL) would be highly useful for developing functional markers and comparing QTL results across multiple independent studies. The objectives of the present study were to map and characterize QTL associated with nine agronomic and end-use quality traits (tillering ability, plant height, lodging, grain yield, grain protein content, thousand kernel weight, test weight, sedimentation volume, and falling number) in hard red spring wheat recombinant inbred lines (RILs) using the International Wheat Genome Sequencing Consortium (IWGSC) RefSeq v2.0 physical map. We evaluated a total of 698 RILs from four populations derived from crosses involving seven parents at 3-8 conventionally (high N) and organically (low N) managed field environments. Using the phenotypic data combined across all environments per management, and the physical map between 1058 and 6526 markers per population, we identified 152 QTL associated with the nine traits, of which 29 had moderate and 2 with major effects. Forty-nine of the 152 QTL mapped across 22 QTL hotspot regions with each region coincident to 2-6 traits. Some of the QTL hotspots were physically located close to known genes. QSv.dms-1A and QPht.dms-4B.1 individually explained up to 37% and 58% of the variation in sedimentation volume and plant height, respectively, and had very large LOD scores that varied from 19.0 to 35.7 and from 16.7 to 55.9, respectively. We consistently detected both QTL in the combined and all individual environments, laying solid ground for further characterization and possibly for cloning.


Subject(s)
Chromosome Mapping , Quantitative Trait Loci , Triticum/genetics , Crosses, Genetic , Genetic Variation , Genotype , Phenotype
3.
Plants (Basel) ; 10(5)2021 Apr 23.
Article in English | MEDLINE | ID: mdl-33922551

ABSTRACT

In previous studies, we reported quantitative trait loci (QTL) associated with the heading, flowering, and maturity time in four hard red spring wheat recombinant inbred line (RIL) populations but the results are scattered in population-specific genetic maps, which is challenging to exploit efficiently in breeding. Here, we mapped and characterized QTL associated with these three earliness traits using the International Wheat Genome Sequencing Consortium (IWGSC) RefSeq v2.0 physical map. Our data consisted of (i) 6526 single nucleotide polymorphisms (SNPs) and two traits evaluated at five conventionally managed environments in the 'Cutler' × 'AC Barrie' population; (ii) 3158 SNPs and two traits evaluated across three organic and seven conventional managements in the 'Attila' × 'CDC Go' population; (iii) 5731 SilicoDArT and SNP markers and the three traits evaluated at four conventional and organic management systems in the 'Peace' × 'Carberry' population; and (iv) 1058 SNPs and two traits evaluated across two conventionally and organically managed environments in the 'Peace' × 'CDC Stanley' population. Using composite interval mapping, the phenotypic data across all environments, and the IWGSC RefSeq v2.0 physical maps, we identified a total of 44 QTL associated with days to heading (11), flowering (10), and maturity (23). Fifteen of the 44 QTL were common to both conventional and organic management systems, and the remaining QTL were specific to either the conventional (21) or organic (8) management systems. Some QTL harbor known genes, including the Vrn-A1, Vrn-B1, Rht-A1, and Rht-B1 that regulate photoperiodism, flowering time, and plant height in wheat, which lays a solid basis for cloning and further characterization.

4.
PLoS One ; 11(8): e0160623, 2016.
Article in English | MEDLINE | ID: mdl-27513976

ABSTRACT

We recently reported three earliness per se quantitative trait loci (QTL) associated with flowering and maturity in a recombinant inbred lines (RILs) population derived from a cross between the spring wheat (Triticum aestivum L.) cultivars 'Cutler' and 'AC Barrie' using 488 microsatellite and diversity arrays technology (DArT) markers. Here, we present QTLs associated with flowering time, maturity, plant height, and grain yield using high density single nucleotide polymorphic (SNP) markers in the same population. A mapping population of 158 RILs and the two parents were evaluated at five environments for flowering, maturity, plant height and grain yield under field conditions, at two greenhouse environments for flowering, and genotyped with a subset of 1809 SNPs out of the 90K SNP array and 2 functional markers (Ppd-D1 and Rht-D1). Using composite interval mapping on the combined phenotype data across all environments, we identified a total of 19 QTLs associated with flowering time in greenhouse (5), and field (6) conditions, maturity (5), grain yield (2) and plant height (1). We mapped these QTLs on 8 chromosomes and they individually explained between 6.3 and 37.8% of the phenotypic variation. Four of the 19 QTLs were associated with multiple traits, including a QTL on 2D associated with flowering, maturity and grain yield; two QTLs on 4A and 7A associated with flowering and maturity, and another QTL on 4D associated with maturity and plant height. However, only the QTLs on both 2D and 4D had major effects, and they mapped adjacent to well-known photoperiod response Ppd-D1 and height reducing Rht-D1 genes, respectively. The QTL on 2D reduced flowering and maturity time up to 5 days with a yield penalty of 436 kg ha-1, while the QTL on 4D reduced plant height by 13 cm, but increased maturity by 2 days. The high density SNPs allowed us to map eight moderate effect, two major effect, and nine minor effect QTLs that were not identified in our previous study using microsatellite and DArT markers. Results from this study provide additional information to wheat researchers developing early maturing and short stature spring wheat cultivars.


Subject(s)
Quantitative Trait Loci , Triticum/genetics , Chromosome Mapping , Chromosomes, Plant , Genotype , Phenotype , Plant Development/genetics , Polymorphism, Single Nucleotide , Triticum/growth & development
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