Allelic response of yield component traits to resource availability in spring wheat.

KEY MESSAGE: Investigation of resource availability on allele effects for four yield component quantitative trait loci provides guidance for the improvement of grain yield in high and low yielding environments. A greater understanding of grain yield (GY) and yield component traits in spring wheat may increase selection efficiency for improved GY in high and low yielding environments. The objective of this study was to determine allelic response of four yield component quantitative trait loci (QTL) to variable resource levels which were manipulated by varying intraspecific plant competition and seeding density. The four QTL investigated in this study had been previously identified as impacting specific yield components. They included QTn.mst-6B for productive tiller number (PTN), WAPO-A1 for spikelet number per spike (SNS), and QGw.mst-3B and TaGW2-A1 for kernel weight (KWT). Near-isogenic lines for each of the four QTL were grown in multiple locations with three competition (border, no-border and space-planted) and two seeding densities (normal 216 seeds m-2 and low 76 seeds m-2). Allele response at QTn.mst-6B was driven by changes in resource availability, whereas allele response at WAPO-A1 and TaGW2-A1 was relatively unaffected by resource availability. The QTn.mst-6B.1 allele at QTn.mst-6B conferred PTN plasticity resulting in significant GY increases in high resource environments. The gw2-A1 allele at TaGW2-A1 significantly increased KWT, SNS and GPC offering a source of GY improvement without negatively impacting end-use quality. QGw.mst-3B allelic variation did not significantly impact KWT but did significantly impact SPS. Treatment effects in both experiments often resulted in significant positive impacts on GY and yield component traits when resource availability was increased. Results provide guidance for leveraging yield component QTL to improve GY performance in high- and low-yield environments.

Analysis of recombinant inbred line populations derived from wheat landraces to identify new genes for wheat stem sawfly resistance.

Wheat landrace accessions were chosen from areas of the world with historical European wheat stem sawfly (Cephus pygmaeus L.) selection pressure to develop six recombinant inbred line (RIL) populations. Molecular maps were constructed, and resistance due to antibiosis and antixenosis was assessed at sites in Montana naturally infested by Cephus cinctus Norton, the wheat stem sawfly (WSS). Novel QTLs were identified along with QTL previously identified in elite germplasm. A newly identified QTL on chromosome 1B provided a new source for pith-filled solid stems. An allele for resistance on chromosome 4A unrelated to solid stems was identified in four of the six RIL populations. A landrace from Turkey, PI 166471, contained alleles at three QTLs causing high levels of larval mortality. None of the QTLs were related to stem solidness, but their combined effect provided resistance similar to that observed in a solid-stemmed check cultivar. These results show the utility of genetic populations derived from geographically targeted landrace accessions to identify new alleles for insect resistance. New PCR-based molecular markers were developed for introgression of novel alleles for WSS resistance into elite lines. Comparison of results with previous analysis of elite cultivars addresses changes in allele frequencies during the wheat breeding process.

Nucleotide diversity maps reveal variation in diversity among wheat genomes and chromosomes.

BACKGROUND: A genome-wide assessment of nucleotide diversity in a polyploid species must minimize the inclusion of homoeologous sequences into diversity estimates and reliably allocate individual haplotypes into their respective genomes. The same requirements complicate the development and deployment of single nucleotide polymorphism (SNP) markers in polyploid species. We report here a strategy that satisfies these requirements and deploy it in the sequencing of genes in cultivated hexaploid wheat (Triticum aestivum, genomes AABBDD) and wild tetraploid wheat (Triticum turgidum ssp. dicoccoides, genomes AABB) from the putative site of wheat domestication in Turkey. Data are used to assess the distribution of diversity among and within wheat genomes and to develop a panel of SNP markers for polyploid wheat. RESULTS: Nucleotide diversity was estimated in 2114 wheat genes and was similar between the A and B genomes and reduced in the D genome. Within a genome, diversity was diminished on some chromosomes. Low diversity was always accompanied by an excess of rare alleles. A total of 5,471 SNPs was discovered in 1791 wheat genes. Totals of 1,271, 1,218, and 2,203 SNPs were discovered in 488, 463, and 641 genes of wheat putative diploid ancestors, T. urartu, Aegilops speltoides, and Ae. tauschii, respectively. A public database containing genome-specific primers, SNPs, and other information was constructed. A total of 987 genes with nucleotide diversity estimated in one or more of the wheat genomes was placed on an Ae. tauschii genetic map, and the map was superimposed on wheat deletion-bin maps. The agreement between the maps was assessed. CONCLUSIONS: In a young polyploid, exemplified by T. aestivum, ancestral species are the primary source of genetic diversity. Low effective recombination due to self-pollination and a genetic mechanism precluding homoeologous chromosome pairing during polyploid meiosis can lead to the loss of diversity from large chromosomal regions. The net effect of these factors in T. aestivum is large variation in diversity among genomes and chromosomes, which impacts the development of SNP markers and their practical utility. Accumulation of new mutations in older polyploid species, such as wild emmer, results in increased diversity and its more uniform distribution across the genome.

Large-scale proteome investigation in wild relatives (A, B, and D genomes) of wheat.

Large-scale proteomics of three wild relatives of wheat grain (A, B, and D genomes) were analyzed by using multidimensional protein identification technology coupled to liquid chromatography quadruple mass spectrometry. A total of 1568 (peptide match ≥1) and 255 (peptide match ≥2) unique proteins were detected and classified, which represents the most wide-ranging proteomic exploitation to date. The development of standard proteomes exhibiting all of the proteins involved in normal physiology will facilitate the delineation of disease/defense, metabolism, energy metabolism, and protein synthesis. A relative proteome exploration of the expression patterns indicates that proteins are involved in abiotic and biotic stress. Functional category analysis indicates that these differentially expressed proteins are mainly involved in disease/defense (15.38%, 21.26%, and 16.78%), metabolism (8.39%, 12.07%, and 14.09%), energy metabolism (11.19%, 11.49%, and 13.42%), protein synthesis (9.09%, 9.20%, and 8.72%), cell growth and division (9.09%, 4.60%, and 6.04%), cellular organization (4.20%, 5.75%, and 5.37%), development (6.29%, 2.87%, 3.36%), folding and stability (6.29%, 8.62%, and 8.05%), signal transduction (11.19%, 7.47%, and 8.05%), storage protein (4.20%, 1.72%, and 2.01%), transcription (5.59%, 5.17%, and 4.03%), and transport facilitation (1.40%, 1.15%, and 3.36%) in A, B, and D genomes, respectively. Here, we reported genome-specific protein interaction network using Cytoscape software, which provides further insight into the molecular functions and mechanism of biochemical pathways. We provide a promising understanding about the expressed proteins and protein functions. Our approach should be applicable as a marker to assist in breeding or gene transfer for quality and stress research of cultivated wheat.