In their manuscript, Ahmed and colleagues describe their high-quality genome assemblies of wild and domesticated einkorn wheat. These assemblies are state-of-the-art, showing high levels of contiguity and completeness. This is a substantial step forward for wheat genomics as previous efforts toward genome assembly have been challenged by the exceptional abundance of repetitive sequences and the large genome sizes of the species. While einkorn wheat is domesticated itself, it is also closely related to a genome donor to both tetraploid and hexaploid domesticated wheat species, making assemblies of einkorn broadly relevant to wheat improvement. Beyond the resources provided by their genome assemblies and gene model/TE annotations, the authors generate resequencing data for hundreds of domesticated and wild einkorn individuals and leverage these data to test hypotheses of einkorn domestication and post-domestication introgression. They also document centromere shifts and the presence of large structural rearrangements within einkorn genomes. This investigation should move the field forward and the high-quality genomics and population genomic analyses will be of interest and serve as an example for researchers working broadly across species. Below I provide suggestions the authors may wish to incorporate into their paper prior to publication.

Einkorn genomics sheds light on history of the oldest domesticated wheat

Wheat (Triticum aestivum) is a staple food for about 40% of the world's population. As the global population has grown and living standards improved, high yield and improved nutritional quality have become the main targets for wheat breeding. However, wheat production has been compromised by global warming through the more frequent occurrence of extreme temperature events, which have increased water scarcity, aggravated soil salinization, caused plants to be more vulnerable to diseases, and directly reduced plant fertility and suppressed yield. One promising option to address these challenges is the genetic improvement of wheat for enhanced resistance to environmental stress. Several decades of progress in genomics and genetic engineering has tremendously advanced our understanding of the molecular and genetic mechanisms underlying abiotic and biotic stress responses in wheat. These advances have heralded what might be considered a "golden age" of functional genomics for the genetic improvement of wheat. Here, we summarize the current knowledge on the molecular and genetic basis of wheat resistance to abiotic and biotic stresses, including the QTLs/genes involved, their functional and regulatory mechanisms, and strategies for genetic modification of wheat for improved stress resistance. In addition, we also provide perspectives on some key challenges that need to be addressed. 

Wheat adaptation to environmental stresses under climate change: Molecular basis and genetic improvement.

<h2>Abstract</h2> Despite recent progress in crop genomics studies, the genomic changes brought about by modern breeding selection are still poorly understood, thus hampering genomics-assisted breeding, especially in polyploid crops with compound genomes such as common wheat (<i>Triticum aestivum</i>). In this work, we constructed genome resources for the modern elite common wheat variety Aikang 58 (AK58). Comparative genomics between AK58 and the landrace cultivar Chinese Spring (CS) shed light on genomic changes that occurred through recent varietal improvement. We also explored subgenome diploidization and divergence in common wheat and developed a homoeologous locus–based genome-wide association study (HGWAS) approach, which was more effective than single homoeolog–based GWAS in unraveling agronomic trait–associated loci. A total of 123 major HGWAS loci were detected using a genetic population derived from AK58 and CS. Elite homoeologous haplotypes (HHs), formed by combinations of subgenomic homoeologs of the associated loci, were found in both parents and progeny, and many could substantially improve wheat yield and related traits. We built a website where users can download genome assembly sequence and annotation data for AK58, perform blast analysis, and run JBrowse. Our work enriches genome resources for wheat, provides new insights into genomic changes during modern wheat improvement, and suggests that efficient mining of elite HHs can make a substantial contribution to genomics-assisted breeding in common wheat and other polyploid crops. 

Genome resources for the elite bread wheat cultivar Aikang 58 and mining of elite homeologous haplotypes for accelerating wheat improvement.

Breeding has dramatically changed the plant architecture of wheat (Triticum aestivum), resulting in the development of high-yielding varieties adapted to modern farming systems. However, how wheat breeding shaped the genomic architecture of this crop remains poorly understood. Here, we performed a comprehensive comparative analysis of a whole-genome resequencing panel of 355 common wheat accessions (representing diverse landraces and modern cultivars from China and the United States) at the phenotypic and genomic levels. The genetic diversity of modern wheat cultivars was clearly reduced compared to landraces. Consistent with these genetic changes, most phenotypes of cultivars from China and the United States were significantly altered. Of the 21 agronomic traits investigated, 8 showed convergent changes between the 2 countries. Moreover, of the 207 loci associated with these 21 traits, more than half overlapped with genomic regions that showed evidence of selection. The distribution of selected loci between the Chinese and American cultivars suggests that breeding for increased productivity in these 2 regions was accomplished by pyramiding both shared and region-specific variants. This work provides a framework to understand the genetic architecture of the adaptation of wheat to diverse agricultural production environments, as well as guidelines for optimizing breeding strategies to design better wheat varieties. 

Whole-genome sequencing of diverse wheat accessions uncovers genetic changes during modern breeding in China and the United States.

It is of considerable concern to establish chiral detection methods for revealing enantioselective interactions among chiral molecules. Surface-enhanced Raman scattering (SERS) spectroscopy is sensitive to molecular interaction due to bond variations. However, its application in chiral detection is underexplored. Inspired by the chiral selectivity toward glucose and amino acids in life, we herein propose a SERS strategy based on molecular interactions for the discrimination of d- and l-glucose (Glu) using chiral phenylalanine (Phe) decorated on gold nanoparticles as a chirality selector and Raman reporter. Interestingly, the SERS signal of l-Phe is enhanced by d-Glu but suppressed by l-Glu. In contrast, the SERS signal of d-Phe is increased by l-Glu but decreased by d-Glu. According to the above-observed intensity change (ΔI) of the SERS signal of Phe induced by Glu, it is easy to determine the chiral configurations (judged by the positive or negative sign of ΔI), enantiomeric excess (ee) values, and concentrations (estimated by the magnitude of ΔI) of Glu. Taking advantage of the high SERS enhancement and opposite enantiomeric effects on SERS signals, the proposed strategy enables enantiomeric discrimination at a low Glu concentration (10-6 mol/L) and is further exerted for the noninvasive detection of d-/l-Glu in saliva samples. In contrast, the common chiroptical analysis tool of circular dichroism (CD) spectroscopy failed to directly detect Glu enantiomers.

Chiral Detection of Glucose: An Amino Acid-Assisted Surface-Enhanced Raman Scattering Strategy Showing Opposite Enantiomeric Effects on SERS Signals.

Population genomics unravels the Holocene history of bread wheat and its relatives

Chiral transition metal oxides nanoparticles (NPs) with tunable optical properties are widely accepted as promising toolbox for chiral recognition, stereoselective synthesis, and chiroptical devices. Herein, chirality‐based strategy is presented for discrimination of d ‐glucose from its enantiomer through a cooperative synergy between chiral cysteine capped MoO2 NPs and the glucose oxidase nanosystem. The valence‐state‐dependent chirality induced by metal‐ligand charge transfer effect is found to be ultrasensitive to its redox environment such as the presence of hydrogen peroxide, which is a key indicator of the stereoselective enzymatic reaction between glucose oxidase and d ‐glucose. With this know‐how, glucose enantiomers can be precisely quantified with a limit of detection of 0.446 µm . Such a chiral bio‐nanosystem would be an ideal platform for a rational design of new types of biosensors, photocatalysts, and chirality‐based nanodevices.

/pdf/metal-to-ligand-charge-transfer-chirality-sensing-of-d-4drttwvpfq.pdf

Metal-to-ligand charge transfer chirality sensing of d-glucose assisted with GOX-based enzymatic reaction

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Ming Zhang

Author Tools

Chat about Author

Papers

Population genomics unravels the Holocene history of bread wheat and its relatives

Metal-to-ligand charge transfer chirality sensing of d-glucose assisted with GOX-based enzymatic reaction