Genome-wide and SNP network analyses reveal genetic control of spikelet sterility and yield-related traits in wheat.

Revealing the genetic factors underlying yield and agronomic traits in wheat are an imperative need for covering the global food demand. Yield boosting requires a deep understanding of the genetic basis of grain yield-related traits (e.g., spikelet fertility and sterility). Here, we have detected much natural variation among ancient hexaploid wheat accessions in twenty-two agronomic traits collected over eight years of field experiments. A genome-wide association study (GWAS) using 15 K single nucleotide polymorphisms (SNPs) was applied to detect the genetic basis of studied traits. Subsequently, the GWAS output was reinforced via other statistical and bioinformatics analyses to detect putative candidate genes. Applying the genome-wide SNP-phenotype network defined the most decisive SNPs underlying the traits. Six pivotal SNPs, co-located physically within the genes encoding enzymes, hormone response, metal ion transport, and response to oxidative stress have been identified. Of these, metal ion transport and Gibberellin 2-oxidases (GA2oxs) genes showed strong involvement in controlling the spikelet sterility, which had not been reported previously in wheat. SNP-gene haplotype analysis confirmed that these SNPs influence spikelet sterility, especially the SNP co-located on the exon of the GA2ox gene. Interestingly, these genes were highly expressed in the grain and spike, demonstrating their pivotal role in controlling the trait. The integrative analysis strategy applied in this study, including GWAS, SNP-phenotype network, SNP-gene haplotype, expression analysis, and genome-wide prediction (GP), empower the identification of functional SNPs and causal genes. GP outputs obtained in this study are encouraging for the implementation of the traits to accelerate yield improvement by making an early prediction of complex yield-related traits in wheat. Our findings demonstrate the usefulness of the ancient wheat material as a valuable resource for yield-boosting. This is the first comprehensive genome-wide analysis for spikelet sterility in wheat, and the results provide insights into yield improvement.

Genome-Wide Association Mapping of Major Root Length QTLs Under PEG Induced Water Stress in Wheat.

Roots are vital plant organs that determine adaptation to various soil conditions. The present study evaluated a core winter wheat collection for rooting depth under PEG induced early stage water stress and non-stress growing conditions. Analysis of phenotypic data indicated highly significant (p < 0.01) variation among genotypes. Broad sense heritability of 59 and 73% with corresponding genetic gains of 7.6 and 9.7 (5% selection intensity) were found under non-stress and stress conditions, respectively. The test genotypes were grouped in to three distinct clusters using unweighted pair group method with arithmetic mean (UPGMA) clustering based on maximum Euclidian distance. The first three principal components gave optimum mixed linear model for genome wide association study (GWAS). Linkage disequilibrium (LD) analysis showed significant LD (p < 0.05) amongst 15% of total marker pairs (25,125). Nearly 16% of the significant LDs were among inter chromosomal marker pairs. GWAS revealed five significant root length QTLs spread across four chromosomes. None of the identified QTLs were common between the two growing conditions. Stress specific QTLs, combined explaining 31% of phenotypic variation were located on chromosomes 2B (wPt6278) and 3B (wPt1159). Similarly, two of the three QTLs (wPt0021 and wPt8890) identified under the non-stress condition were found on chromosomes 3B and 5B, respectively. The B genome showed significant importance in controlling root growth both under stress and non-stress conditions. The identified markers can potentially be validated and used for marker assisted selection.

Molecular markers in management of ex situ PGR-a case study.

Worldwide germplasm collections contain about 7.4 million accessions of plant genetic resources for food and agriculture. One of the 10 largest ex situ genebanks of our globe is located at the Leibniz Institute of Plant Genetics and Crop Plant Research in Gatersleben, Germany. Molecular tools have been used for various gene bank management practices including characterization and utilization of the germplasm. The results on genetic integrity of longterm- stored gene bank accessions of wheat (self-pollinating) and rye (open-pollinating) cereal crops revealed a high degree of identity for wheat. In contrast, the out-pollinating accessions of rye exhibited shifts in allele frequencies. The genetic diversity of wheat and barley germplasm collected at intervals of 40 to 50 years in comparable geographical regions showed qualitative rather than a quantitative change in diversity. The inter- and intraspecific variation of seed longevity was analysed and differences were detected. Genetic studies in barley, wheat and oilseed rape revealed numerous QTL, indicating the complex and quantitative nature of seed longevity. Some of the loci identified were in genomic regions that co-localize with genes determining agronomic traits such as spike architecture or biotic and abiotic stress response. Finally, a genome-wide association mapping analysis of a core collection of wheat for flowering time was performed using diversity array technology (DArT) markers. Maker trait associations were detected in genomic regions where major genes or QTL have been described earlier. In addition, new loci were also detected, providing opportunities to monitor genetic variation for crop improvement.

Population structure in a wheat core collection and genomic loci associated with yield under contrasting environments.

A set of 96 winter wheat accessions sampled from a variety of geographic origins, including cultivars and breeding lines, were characterized with 46 genome-wide SSR loci for genetic diversity and population structure. The genetic diversity within these accessions was examined using a genetic distance-based and a model-based clustering method. The model-based analysis identified an underlying population structure comprising of four distinct sub-populations which corresponded well with distance-based groupings. Information on the population structure is taken into account in an association mapping study of grain yield from a 3-years field trial incorporating fully irrigated, rainfed and drought stress treatments. A total of 21 marker-grain yield associations (P < 0.01) were identified with nine SSR markers. Most associations were detected only in one to three environments (treatment/year combination), with an average R ( 2 ) value around 13 %. However, marker gwm484 (on chromosome 2D) was associated with yield in six environments, including irrigated, rainfed and drought stress treatments, suggesting it could be used to improve grain yield across a range of environments. Variation in grain yield at this locus was associated with earliness, early vigour, kernels per spikelet and harvest index. Microsatellite locus psp3200 (on chromosome 6D) was associated with yield in dry and hot environments, which was related to earliness, early vigour, productive tillering and total biomass per plant. Partial least squares regression, with nine environmental factors, showed that precipitation from tillering to maturity was the main environmental factor causing marker × environment associations for grain yield.

Genetic and association mapping study of wheat agronomic traits under contrasting water regimes.

Genetic analyses and association mapping were performed on a winter wheat core collection of 96 accessions sampled from a variety of geographic origins. Twenty-four agronomic traits were evaluated over 3 years under fully irrigated, rainfed and drought treatments. Grain yield was the most sensitive trait to water deficit and was highly correlated with above-ground biomass per plant and number of kernels per m(2). The germplasm was structured into four subpopulations. The association of 46 SSR loci distributed throughout the wheat genome with yield and agronomic traits was analyzed using a general linear model, where subpopulation information was used to control false-positive or spurious marker-trait associations (MTAs). A total of 26, 21 and 29 significant (P < 0.001) MTAs were identified in irrigated, rainfed and drought treatments, respectively. The marker effects ranged from 14.0 to 50.8%. Combined across all treatments, 34 significant (P < 0.001) MTAs were identified with nine markers, and R(2) ranged from 14.5 to 50.2%. Marker psp3200 (6DS) and particularly gwm484 (2DS) were associated with many significant MTAs in each treatment and explained the greatest proportion of phenotypic variation. Although we were not able to recognize any marker related to grain yield under drought stress, a number of MTAs associated with developmental and agronomic traits highly correlated with grain yield under drought were identified.

Genetic diversity of the Novi Sad Wheat Core Collection revealed by microsatellites.

In recent years, considerable emphasis has been placed on the development of microsatellites to be used for a variety of objectives. Parental genetic diversity is a crucial requisition to derive desirable and superior progenies from crossing and selection. In order to determine desirable genotypes for hybridization, 710 wheat genotypes from the Novi Sad Core Collection, originating from 38 countries, have been evaluated during the 1993-2000 period. During those seven growth seasons, 54 agronomical, morphological, physiological and other traits have been evaluated in field and controlled conditions. In each year, the field experiment comprised 3-7 replications, while for each field replication the plot size was 1.2 m(2). Based on the results from this evaluation, 96 genotypes with the highest phenotypic variation for 26 of the very important traits for wheat breeding programmes in Yugoslavia and the UK, were identified for screening with microsatellites. A set of 36 microsatellite markers was used, covering all three wheat genomes and all 42 chromosomes. For the 36 microsatellites, a total of 46 loci and 366 alleles were detected, with the average number of 7.96 alleles per locus. For 35 loci, null alleles were detected. The association of microsatellite data with phenotypic data, for 6 important traits for wheat breeding (stem height, earliness, resistance to leaf rust and powdery mildew, sedimentation value and protein content), as well as the potential for their implementation in marker assisted selection (MAS) in wheat breeding programmes for both Yugoslavia and UK are discussed.