Exploiting the Repetitive Fraction of the Wheat Genome for High-Throughput Single-Nucleotide Polymorphism Discovery and Genotyping

Impact of structural variations and genome partitioning on bread wheat hybrid performance

The agronomical interest of hybrid wheat has long been a matter of debate. Compared to maize where hybrids have been successfully grown for decades, the mixed results obtained in wheat have been attributed at least partially to the lack of heterotic groups. The wheat genome is known to be strongly partitioned and characterized by numerous presence/absence variations and alien introgressions which have not been thoroughly considered in hybrid breeding. The objective was to investigate the relationships between hybrid performance and genomic diversity. For this, we characterized a set of 124 hybrids as well as their 19 female and 16 male parents. Phenotyping for yield and yield components was conducted during two years in three locations. Parental lines were genotyped using a 410 K SNP array as well as through sequence capture of roughly 200,000 loci. This led to the identification of 180 structural variations including presence-absence variations and alien introgressions. Twenty-six of them were associated to hybrid performance through either additivity or dominance effects. While no correlation was observed at the whole genome level, the genetic distance for 25 genomic regions resulting from the structural and functional partitioning of the chromosomes shown positive or negative correlation with agronomic traits including yield. Large introgressions, like the Aegilops ventricosa 2NS-2AS translocation, can correspond to entire chromosomal regions, such as the R1 region, with an impact on yield. Our results suggest hybrid breeding should consider both structural variations and chromosome partitioning rather than maximizing whole-genome genetic distance, and according to genomic regions to combine homozygosity and heterozygosity.

Recent Advance in Single-Molecule Fluorescent Biosensors for Tumor Biomarker Detection

The construction of biosensors for specific, sensitive, and rapid detection of tumor biomarkers significantly contributes to biomedical research and early cancer diagnosis. However, conventional assays often involve large sample consumption and poor sensitivity, limiting their further application in real samples. In recent years, single-molecule biosensing has emerged as a robust tool for detecting and characterizing biomarkers due to its unique advantages including simplicity, low sample consumption, ultra-high sensitivity, and rapid assay time. This review summarizes the recent advances in the construction of single-molecule biosensors for the measurement of various tumor biomarkers, including DNAs, DNA modifications, RNAs, and enzymes. We give a comprehensive review about the working principles and practical applications of these single-molecule biosensors. Additionally, we discuss the challenges and limitations of current single-molecule biosensors, and highlight the future directions.

Genetic diversity, linkage disequilibrium, and population structure of tetraploid wheat landraces originating from Europe and Asia

BACKGROUND

Durum wheat is one of the most important crops, especially in the Mediterranean region. Insight into the genetic diversity of germplasm can improve the breeding program management in various traits. This study was done using single nucleotide polymorphisms (SNP) markers to characterize the genetic distinctiveness and differentiation of tetraploid wheat landraces collected from nine European and Asian countries. A sum of 23,334 polymorphic SNPs was detected in 126 tetraploid wheat landraces in relation to the reference genome.

RESULTS

The number of identified SNPs was 11,613 and 11,721 in A and B genomes, respectively. The highest and lowest diversity was on 6B and 6 A chromosomes, respectively. Structure analysis classified the landraces into two distinct subpopulations (K = 2). Evaluating the principal coordinate analysis (PCoA) and weighted pair-group method using arithmetic averages (WPGMA) clustering results demonstrated that landraces (99.2%) are categorized into one of the two chief subpopulations. Therefore, the grouping pattern did not clearly show the presence of a clear pattern of relationships between genetic diversity and their geographical derivation. Part of this result could be due to the historical exchange between different germplasms. Although the result did not separate landraces based on their region of origin, the landraces collected from Iran were classified into the same group and cluster. Analysis of molecular variance (AMOVA) also confirmed the results of population structure. Finally, Durum wheat landraces in some countries, including Turkey, Russia, Ukraine, and Afghanistan, were highly diverse, while others, including Iran and China, were low-diversity.

CONCLUSION

The recent study concluded that the 126 tetraploid wheat genotypes and their GBS-SNP markers are very appropriate for quantitative trait loci (QTLs) mapping and genome-wide association studies (GWAS). The core collection comprises two distinct subpopulations. Subpopulation II genotypes are the most diverse genotypes, and if they possess desired traits, they may be used in future breeding programs. The degree of diversity in the landraces of countries can provide the ground for the improvement of new cultivars with international cooperation. linkage disequilibrium (LD) hotspot distribution across the genome was investigated, which provides useful information about the genomic regions that contain intriguing genes.

Breeding for Economically and Environmentally Sustainable Wheat Varieties: An Integrated Approach from Genomics to Selection

There is currently a strong societal demand for sustainability, quality, and safety in bread wheat production. To address these challenges, new and innovative knowledge, resources, tools, and methods to facilitate breeding are needed. This starts with the development of high throughput genomic tools including single nucleotide polymorphism (SNP) arrays, high density molecular marker maps, and full genome sequences. Such powerful tools are essential to perform genome-wide association studies (GWAS), to implement genomic and phenomic selection, and to characterize the worldwide diversity. This is also useful to breeders to broaden the genetic basis of elite varieties through the introduction of novel sources of genetic diversity. Improvement in varieties particularly relies on the detection of genomic regions involved in agronomical traits including tolerance to biotic (diseases and pests) and abiotic (drought, nutrient deficiency, high temperature) stresses. When enough resolution is achieved, this can result in the identification of candidate genes that could further be characterized to identify relevant alleles. Breeding must also now be approached through in silico modeling to simulate plant development, investigate genotype × environment interactions, and introduce marker-trait linkage information in the models to better implement genomic selection. Breeders must be aware of new developments and the information must be made available to the world wheat community to develop new high-yielding varieties that can meet the challenge of higher wheat production in a sustainable and fluctuating agricultural context. In this review, we compiled all knowledge and tools produced during the BREEDWHEAT project to show how they may contribute to face this challenge in the coming years.

Marker-based crop model-assisted ideotype design to improve avoidance of abiotic stress in bread wheat

Wheat phenology allows escape from seasonal abiotic stresses including frosts and high temperatures, the latter being forecast to increase with climate change. The use of marker-based crop models to identify ideotypes has been proposed to select genotypes adapted to specific weather and management conditions and anticipate climate change. In this study, a marker-based crop model for wheat phenology was calibrated and tested. Climate analysis of 30 years of historical weather data in 72 locations representing the main wheat production areas in France was performed. We carried out marker-based crop model simulations for 1019 wheat cultivars and three sowing dates, which allowed calculation of genotypic stress avoidance frequencies of frost and heat stress and identification of ideotypes. The phenology marker-based crop model allowed prediction of large genotypic variations for the beginning of stem elongation (GS30) and heading date (GS55). Prediction accuracy was assessed using untested genotypes and environments, and showed median genotype prediction errors of 8.5 and 4.2 days for GS30 and GS55, respectively. Climate analysis allowed the definition of a low risk period for each location based on the distribution of the last frost and first heat days. Clustering of locations showed three groups with contrasting levels of frost and heat risks. Marker-based crop model simulations showed the need to optimize the genotype depending on sowing date, particularly in high risk environments. An empirical validation of the approach showed that it holds good promises to improve frost and heat stress avoidance.

Genomic analysis of Spanish wheat landraces reveals their variability and potential for breeding

Background

One of the main goals of the plant breeding in the twenty-first century is the development of crop cultivars that can maintain current yields in unfavorable environments. Landraces that have been grown under varying local conditions include genetic diversity that will be essential to achieve this objective. The Center of Plant Genetic Resources of the Spanish Institute for Agriculture Research maintains a broad collection of wheat landraces. These accessions, which are locally adapted to diverse eco-climatic conditions, represent highly valuable materials for breeding. However, their efficient use requires an exhaustive genetic characterization. The overall aim of this study was to assess the diversity and population structure of a selected set of 380 Spanish landraces and 52 reference varieties of bread and durum wheat by high-throughput genotyping.

Results

The DArTseq GBS approach generated 10 K SNPs and 40 K high-quality DArT markers, which were located against the currently available bread and durum wheat reference genomes. The markers with known locations were distributed across all chromosomes with relatively well-balanced genome-wide coverage. The genetic analysis showed that the Spanish wheat landraces were clustered in different groups, thus representing genetic pools providing a range of allelic variation. The subspecies had a major impact on the population structure of the durum wheat landraces, with three distinct clusters that corresponded to subsp. durum, turgidum and dicoccon being identified. The population structure of bread wheat landraces was mainly biased by geographic origin.

Conclusions

The results showed broader genetic diversity in the landraces compared to a reference set that included commercial varieties, and higher divergence between the landraces and the reference set in durum wheat than in bread wheat. The analyses revealed genomic regions whose patterns of variation were markedly different in the landraces and reference varieties, indicating loci that have been under selection during crop improvement, which could help to target breeding efforts. The results obtained from this work will provide a basis for future genome-wide association studies.

Wheat ms5 male-sterility is induced by recessive homoeologous A and D genome non-specific lipid transfer proteins

Nuclear male-sterile mutants with non-conditional, recessive and strictly monogenic inheritance are useful for both hybrid and conventional breeding systems, and have long been a research focus for many crops. In allohexaploid wheat, however, genic redundancy results in rarity of such mutants, with the ethyl methanesulfonate-induced mutant ms5 among the few reported to date. Here, we identify TaMs5 as a glycosylphosphatidylinositol-anchored lipid transfer protein required for normal pollen exine development, and by transgenic complementation demonstrate that TaMs5-A restores fertility to ms5. We show ms5 locates to a centromere-proximal interval and has a sterility inheritance pattern modulated by TaMs5-D but not TaMs5-B. We describe two allelic forms of TaMs5-D, one of which is non-functional and confers mono-factorial inheritance of sterility. The second form is functional but shows incomplete dominance. Consistent with reduced functionality, transcript abundance in developing anthers was found to be lower for TaMs5-D than TaMs5-A. At the 3B homoeolocus, we found only non-functional alleles among 178 diverse hexaploid and tetraploid wheats that include landraces and Triticum dicoccoides. Apparent ubiquity of non-functional TaMs5-B alleles suggests loss-of-function arose early in wheat evolution and, therefore, at most knockout of two homoeoloci is required for sterility. This work provides genetic information, resources and tools required for successful implementation of ms5 sterility in breeding systems for bread and durum wheats.

DAWN: a resource for yielding insights into the diversity among wheat genomes

BACKGROUND

Democratising the growing body of whole genome sequencing data available for Triticum aestivum (bread wheat) has been impeded by the lack of a genome reference and the large computational requirements for analysing these data sets.

RESULTS

DAWN (Diversity Among Wheat geNomes) integrates data from the T. aestivum Chinese Spring (CS) IWGSC RefSeq v1.0 genome with public WGS and exome data from 17 and 62 accessions respectively, enabling researchers and breeders alike to investigate genotypic differences between wheat accessions at the level of whole chromosomes down to individual genes.

CONCLUSIONS

Using DAWN we show that it is possible to visualise small and large chromosomal deletions, identify haplotypes at a glance and spot the consequences of selective breeding. DAWN allows us to detect the break points of alien introgression segments brought into an accession when transferring desired genes. Furthermore, we can find possible explanations for reduced recombination in parts of a chromosome, we can predict regions with linkage drag, and also look at diversity in centromeric regions.

High throughput SNP discovery and genotyping in hexaploid wheat

Because of their abundance and their amenability to high-throughput genotyping techniques, Single Nucleotide Polymorphisms (SNPs) are powerful tools for efficient genetics and genomics studies, including characterization of genetic resources, genome-wide association studies and genomic selection. In wheat, most of the previous SNP discovery initiatives targeted the coding fraction, leaving almost 98% of the wheat genome largely unexploited. Here we report on the use of whole-genome resequencing data from eight wheat lines to mine for SNPs in the genic, the repetitive and non-repetitive intergenic fractions of the wheat genome. Eventually, we identified 3.3 million SNPs, 49% being located on the B-genome, 41% on the A-genome and 10% on the D-genome. We also describe the development of the TaBW280K high-throughput genotyping array containing 280,226 SNPs. Performance of this chip was examined by genotyping a set of 96 wheat accessions representing the worldwide diversity. Sixty-nine percent of the SNPs can be efficiently scored, half of them showing a diploid-like clustering. The TaBW280K was proven to be a very efficient tool for diversity analyses, as well as for breeding as it can discriminate between closely related elite varieties. Finally, the TaBW280K array was used to genotype a population derived from a cross between Chinese Spring and Renan, leading to the construction a dense genetic map comprising 83,721 markers. The results described here will provide the wheat community with powerful tools for both basic and applied research.