Biogenic synthesis of ZnO-NPs using P. somniferum.

Drought being a yield limiting factor has become a major threat to international food security. It is a complex trait and drought tolerance response is carried out by various genes, transcription factors (TFs), microRNAs (miRNAs), hormones, proteins, co-factors, ions, and metabolites. This complexity has limited the development of wheat cultivars for drought tolerance by classical breeding. However, attempts have been made to fill the lost genetic diversity by crossing wheat with wild wheat relatives. In recent years, several molecular markers including single nucleotide polymorphisms (SNPs) and quantitative trait loci (QTLs) associated with genes for drought signaling pathways have been reported. Screening of large wheat collections by marker assisted selection (MAS) and transformation of wheat with different genes/TFs has improved drought signaling pathways and tolerance. Several miRNAs also provide drought tolerance to wheat by regulating various TFs/genes. Emergence of OMICS techniques including transcriptomics, proteomics, metabolomics, and ionomics has helped to identify and characterize the genes, proteins, metabolites, and ions involved in drought signaling pathways. Together, all these efforts helped in understanding the complex drought tolerance mechanism. Here, we have reviewed the advances in wide hybridization, MAS, QTL mapping, miRNAs, transgenic technique, genome editing system, and above mentioned functional genomics tools for identification and utility of signaling molecules for improvement in wheat drought tolerance.

Aptamers are target specific ssDNA, RNA or peptide sequences generated by an in vitro selection and amplification method called SELEX (Systematic Evolution of Ligands by EXponential Enrichment), which involves repetitive cycles of binding, recovery and amplification steps. Aptamers have the ability to bind with a variety of targets such as drugs, proteins, heavy metals, pathogens with high specificity and selectivity. Aptamers are similar to monoclonal antibodies regarding their binding affinities, but they provide a number of advantages to the existing antibody-based detection methods that make the aptamers promising diagnostic and therapeutic tools for the future biomedical and analytical applications. The aim of this review article is to provide an overview of the recent advancements in aptamer screening methods along with a concise description of the major application areas of aptamers including the biomarker discovery, diagnostics, imaging and the nanotechnology.

BackgroundDrought is a lifestyle disease. Plant metabolomics has been exercised for understanding the fine-tuning of the potential pathways to surmount the adverse effects of drought stress. A broad spectrum of morphological and metabolic responses from seven Triticeae species including wild types with different drought tolerance/susceptibility level was investigated under control and water scarcity conditions.ResultsSignificant morphological parameters measured were root length, surface area, average root diameter and overall root development. Principal Component Analysis, Partial Least-Squares-Discriminant Analysis and Hierarchical Cluster Analysis were applied to the metabolomic data obtained by Gas Chromatography-Mass Spectrometry technique in order to determine the important metabolites of the drought tolerance across seven different Triticeae species. The metabolites showing significant accumulation under the drought stress were considered as the key metabolites and correlated with potential biochemical pathways, enzymes or gene locations for a better understanding of the tolerance mechanisms. In all tested species, 45 significantly active metabolites with possible roles in drought stress were identified. Twenty-one metabolites out of forty-five including sugars, amino acids, organic acids and low molecular weight compounds increased in both leaf and root samples of TR39477, IG132864 and Bolal under the drought stress, contrasting to TTD-22, Tosunbey, Ligustica and Meyeri samples. Three metabolites including succinate, aspartate and trehalose were selected for further genome analysis due to their increased levels in TR39477, IG132864, and Bolal upon drought stress treatment as well as their significant role in energy producing biochemical pathways.ConclusionThese results demonstrated that the genotypes with high drought tolerance skills, especially wild emmer wheat, have a great potential to be a genetic model system for experiments aiming to validate metabolomics–genomics networks.Electronic supplementary materialThe online version of this article (10.1186/s12864-017-4321-2) contains supplementary material, which is available to authorized users.

Nanoparticles typically have dimensions of less than 100 nm. Scientists around the world have recently become interested in nanotechnology because of its potential applications in a wide range of fields, including catalysis, gas sensing, renewable energy, electronics, medicine, diagnostics, medication delivery, cosmetics, the construction industry, and the food industry. The sizes and forms of nanoparticles (NPs) are the primary determinants of their properties. Nanoparticles’ unique characteristics may be explored for use in electronics (transistors, LEDs, reusable catalysts), energy (oil recovery), medicine (imaging, tumor detection, drug administration), and more. For the aforementioned applications, the synthesis of nanoparticles with an appropriate size, structure, monodispersity, and morphology is essential. New procedures have been developed in nanotechnology that are safe for the environment and can be used to reliably create nanoparticles and nanomaterials. This research aims to illustrate top-down and bottom-up strategies for nanomaterial production, and numerous characterization methodologies, nanoparticle features, and sector-specific applications of nanotechnology.

The use of perovskites in photovoltaic and related industries has gained tremendous success over the last decade. However, there are still obstacles to overcome in terms of boosting their performance...

Recent technological advances in next-generation sequencing (NGS) technologies have dramatically reduced the cost of DNA sequencing, allowing species with large and complex genomes to be sequenced. Although bread wheat (Triticum aestivum L.) is one of the world’s most important food crops, efficient exploitation of molecular marker-assisted breeding approaches has lagged behind that achieved in other crop species, due to its large polyploid genome. However, an international public–private effort spanning 9 years reported over 65% draft genome of bread wheat in 2014, and finally, after more than a decade culminated in the release of a gold-standard, fully annotated reference wheat-genome assembly in 2018. Shortly thereafter, in 2020, the genome of assemblies of additional 15 global wheat accessions was released. As a result, wheat has now entered into the pan-genomic era, where basic resources can be efficiently exploited. Wheat genotyping with a few hundred markers has been replaced by genotyping arrays, capable of characterizing hundreds of wheat lines, using thousands of markers, providing fast, relatively inexpensive, and reliable data for exploitation in wheat breeding. These advances have opened up new opportunities for marker-assisted selection (MAS) and genomic selection (GS) in wheat. Herein, we review the advances and perspectives in wheat genetics and genomics, with a focus on key traits, including grain yield, yield-related traits, end-use quality, and resistance to biotic and abiotic stresses. We also focus on reported candidate genes cloned and linked to traits of interest. Furthermore, we report on the improvement in the aforementioned quantitative traits, through the use of (i) clustered regularly interspaced short-palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9)-mediated gene-editing and (ii) positional cloning methods, and of genomic selection. Finally, we examine the utilization of genomics for the next-generation wheat breeding, providing a practical example of using in silico bioinformatics tools that are based on the wheat reference-genome sequence.

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