The availability of information on the genetic diversity and population structure in wheat (Triticum aestivum L.) breeding lines will help wheat breeders to better use their genetic resources and manage genetic variation in their breeding program. The recent advances in sequencing technology provide the opportunity to identify tens or hundreds of thousands of single nucleotide polymorphism (SNPs) in large genome species (e.g., wheat). These SNPs can be utilized for understanding genetic diversity and performing genome wide association studies (GWAS) for complex traits. In this study, the genetic diversity and population structure were investigated in a set of 230 genotypes (F3:6) derived from various crosses as a prerequisite for GWAS and genomic selection. Genotyping-by-sequencing provided 25,566 high-quality SNPs. The polymorphism information content (PIC) across chromosomes ranged from 0.09 to 0.37 with an average of 0.23. The distribution of SNPs markers on the 21 chromosomes ranged from 319 on chromosome 3D to 2,370 on chromosome 3B. The analysis of population structure revealed three subpopulations (G1, G2, and G3). Analysis of molecular variance identified 8% variance among and 92% within subpopulations. Of the three subpopulations, G2 had the highest level of genetic diversity based on three genetic diversity indices: Shannon’s information index (I) = 0.494, diversity index (h) = 0.328 and unbiased diversity index (uh) = 0.331, while G3 had lowest level of genetic diversity (I = 0.348, h = 0.226 and uh = 0.236). This high genetic diversity identified among the subpopulations can be used to develop new wheat cultivars.

BackgroundThe homeodomain leucine zipper (HD-Zip) transcription factor family is one of the largest plant specific superfamilies, and includes genes with roles in modulation of plant growth and response to environmental stresses. Many HD-Zip genes are characterized in Arabidopsis (Arabidopsis thaliana), and members of the family are being investigated for abiotic stress responses in rice (Oryza sativa), maize (Zea mays), poplar (Populus trichocarpa) and cucumber (Cucmis sativus). Findings in these species suggest HD-Zip genes as high priority candidates for crop improvement.ResultsIn this study we have identified members of the HD-Zip gene family in soybean cv. ‘Williams 82’, and characterized their expression under dehydration and salt stress. Homology searches with BLASTP and Hidden Markov Model guided sequence alignments identified 101 HD-Zip genes in the soybean genome. Phylogeny reconstruction coupled with domain and gene structure analyses using soybean, Arabidopsis, rice, grape (Vitis vinifera), and Medicago truncatula homologues enabled placement of these sequences into four previously described subfamilies. Of the 101 HD-Zip genes identified in soybean, 88 exist as whole-genome duplication-derived gene pairs, indicating high retention of these genes following polyploidy in Glycine ~13 Mya. The HD-Zip genes exhibit ubiquitous expression patterns across 24 conditions that include 17 tissues of soybean. An RNA-Seq experiment performed to study differential gene expression at 0, 1, 6 and 12 hr soybean roots under dehydration and salt stress identified 20 differentially expressed (DE) genes. Several of these DE genes are orthologs of genes previously reported to play a role under abiotic stress, implying conservation of HD-Zip gene functions across species. Screening of HD-Zip promoters identified transcription factor binding sites that are overrepresented in the DE genes under both dehydration and salt stress, providing further support for the role of HD-Zip genes in abiotic stress responses.ConclusionsWe provide a thorough description of soybean HD-Zip genes, and identify potential candidates with probable roles in dehydration and salt stress. Expression profiles generated for all soybean genes, under dehydration and salt stress, at four time points, will serve as an important resource for the soybean research community, and will aid in understanding plant responses to abiotic stress.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2164-15-950) contains supplementary material, which is available to authorized users.

Synthetic hexaploid wheat (SHW; 2n = 6x = 42, AABBDD, Triticum aestivum L.) is produced from an interspecific cross between durum wheat (2n = 4x = 28, AABB, T. turgidum L.) and goat grass (2n = 2x = 14, DD, Aegilops tauschii Coss.) and is reported to have significant novel alleles-controlling biotic and abiotic stresses resistance. A genome-wide association study (GWAS) was conducted to unravel these loci [marker–trait associations (MTAs)] using 35,648 genotyping-by-sequencing-derived single nucleotide polymorphisms in 123 SHWs. We identified 90 novel MTAs (45, 11, and 34 on the A, B, and D genomes, respectively) and haplotype blocks associated with grain yield and yield-related traits including root traits under drought stress. The phenotypic variance explained by the MTAs ranged from 1.1% to 32.3%. Most of the MTAs (120 out of 194) identified were found in genes, and of these 45 MTAs were in genes annotated as having a potential role in drought stress. This result provides further evidence for the reliability of MTAs identified. The large number of MTAs (53) identified especially on the D-genome demonstrate the potential of SHWs for elucidating the genetic architecture of complex traits and provide an opportunity for further improvement of wheat under rapidly changing climatic conditions.

Winter wheat parents ‘Harry’ (drought tolerant) and ‘Wesley’ (drought susceptible) were used to develop a recombinant inbred population with future goals of identifying genomic regions associated with drought tolerance. To precisely map genomic regions, high-density linkage maps are a prerequisite. In this study genotyping-by- sequencing (GBS) was used to construct the high-density linkage map. The map contained 3,641 markers distributed on 21 chromosomes and spanned 1,959 cM with an average distance of 1.8 cM between markers. The constructed linkage map revealed strong collinearity in marker order across 21 chromosomes with POPSEQ-v2.0, which was based on a high-density linkage map. The reliability of the linkage map for QTL mapping was demonstrated by co-localizing the genes to previously mapped genomic regions for two highly heritable traits, chaff color, and leaf cuticular wax. Applicability of linkage map for QTL mapping of three quantitative traits, flag leaf length, width, and area, identified 21 QTLs in four environments, and QTL expression varied across the environments. Two major stable QTLs, one each for flag leaf length (Qfll.hww-7A) and flag leaf width (Qflw.hww-5A) were identified. The map constructed will facilitate QTL and fine mapping of quantitative traits, map-based cloning, comparative mapping, and in marker-assisted wheat breeding endeavors.

Synthetic hexaploid wheat (SHW; Triticum durum L. × Aegilops tauschii Coss.) is a means of introducing novel genes/genomic regions into bread wheat (T. aestivum L.) and a potential genetic resource for improving grain mineral concentrations. We quantified 10 grain minerals (Ca, Cd, Cu, Co, Fe, Li, Mg, Mn, Ni, and Zn) using an inductively coupled mass spectrometer in 123 SHWs for a genome-wide association study (GWAS). A GWAS with 35,648 single nucleotide polymorphism (SNP) markers identified 92 marker-trait associations (MTAs), of which 60 were novel and 40 were within genes, and the genes underlying 20 MTAs had annotations suggesting a potential role in grain mineral concentration. Twenty-four MTAs on the D-genome were novel and showed the potential of Ae. tauschii for improving grain mineral concentrations such as Ca, Co, Cu, Li, Mg, Mn, and Ni. Interestingly, the large number of novel MTAs (36) identified on the AB genome of these SHWs indicated that there is a lot of variation yet to be explored and to be used in the A and B genome along with the D-genome. Regression analysis identified a positive correlation between a cumulative number of favorable alleles at MTA loci in a genotype and grain mineral concentration. Additionally, we identified multi-traits and stable MTAs and recommended 13 top 10% SHWs with a higher concentration of beneficial grain minerals (Cu, Fe, Mg, Mn, Ni, and Zn), a large number of favorable alleles compared to low ranking genotypes and checks that could be utilized in the breeding program for the genetic biofortification. This study will further enhance our understanding of the genetic architecture of grain minerals in wheat and related cereals.