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The robustness against noise, outliers, and corruption is a crucial issue in image feature extraction. To address this concern, this paper proposes a discriminative low-rank embedding image feature extraction algorithm. Firstly, to enhance the discriminative power of the extracted features, a discriminative term is introduced using label information, obtaining global discriminative information and learning an optimal projection matrix for data dimensionality reduction. Secondly, manifold constraints are incorporated, unifying low-rank embedding and manifold constraints into a single framework to capture the geometric structure of local manifolds while considering both local and global information. Finally, test samples are projected into a lower-dimensional space for classification. Experimental results demonstrate that the proposed method achieves classification accuracies of 95.62%, 95.22%, 86.38%, and 86.54% on the ORL, CMUPIE, AR, and COIL20 datasets, respectively, outperforming dimensionality reduction-based image feature extraction algorithms. [ABSTRACT FROM AUTHOR]

Members of the EPIDERMAL PATTERNING FACTOR-LIKE (EPFL) family play diverse roles in plant growth and development, including the guidance of inflorescence architecture and pedicel length. In this work, we identified and characterized the EFPL gene TaEPFL1 from the wheat pistillody mutant HTS-1. Sequence alignment and phylogenetic analysis indicated that TaEPFL1 belongs to the EPFL1 gene. Quantitative real-time RT-PCR analysis showed that the TaEPFL1 gene is expressed at an abnormally high level in pistillody stamens compared with that in pistils and stamens. Heterologous expression of the TaEPFL1 gene in Arabidopsis caused shortened filaments and pedicels and might reduce the level of AtACO2 gene expression. These results suggest that TaEPFL1 plays an important role in the development of stamen and that overexpression of TaEPFL1 results in abnormal stamens. We deduced that the overexpression of the TaEPFL1 gene may contribute to the homeotic transformation of stamens into pistils or pistil-like structures in wheat. These data offer insights into the molecular mechanism of pistillody mutation in wheat. [ABSTRACT FROM AUTHOR]

WAG-2 is a C-class MADS-box gene, which is orthologous to AGAMOUS ( AG) in Arabidopsis. The AG group C-class MADS-box genes are involved in stamen and pistil identity. In this study, two WAG-2 transcripts, namely, WAG-2f and WAG-2g, were isolated and characterized from Aegilops tauschii. The open reading frames of WAG-2f and WAG-2g were 825 and 822 bp, respectively, encoding 275 and 274 amino acid residues. BLAST searches of partial WAG-2 genomic sequence against the draft sequence of Ae. tauschii genome database revealed the complex structure of WAG-2 gene, which consisted of seven exons and six introns. The WAG-2f and WAG-2g cDNAs were two alternative splicing transcripts. The alternative splicing events were produced by an alternative 5 splice site. The expression level of WAG-2f transcript, which was extremely weak in young spikes of floret primordium formation stage, increased as the spikes developed. The highest expression was observed in the spikes at the anther separation stage. Low expression levels of WAG-2f were also detected at the tetrad stage. The WAG-2g transcript was expressed at all four stages of spike development but at a relatively low level. The expression pattern of the two transcripts was distinctly different during floral development, thereby suggesting a functional divergence. [ABSTRACT FROM AUTHOR]

Genomic selection is a promising molecular breeding strategy enhancing genetic gain per unit time. The objectives of our study were to (1) explore the prediction accuracy of genomic selection for plant height and yield per plant in soybean [Glycine max (L.) Merr.], (2) discuss the relationship between prediction accuracy and numbers of markers, and (3) evaluate the effect of marker preselection based on different methods on the prediction accuracy. Our study is based on a population of 235 soybean varieties which were evaluated for plant height and yield per plant at multiple locations and genotyped by 5361 single nucleotide polymorphism markers. We applied ridge regression best linear unbiased prediction coupled with fivefold cross-validations and evaluated three strategies of marker preselection. For plant height, marker density and marker preselection procedure impacted prediction accuracy only marginally. In contrast, for grain yield, prediction accuracy based on markers selected with a haplotype block analyses-based approach increased by approximately 4 % compared with random or equidistant marker sampling. Thus, applying marker preselection based on haplotype blocks is an interesting option for a cost-efficient implementation of genomic selection for grain yield in soybean breeding. [ABSTRACT FROM AUTHOR]

To understand the molecular mechanism of the three pistils mutation in wheat, two forward subtractive cDNA libraries from two pairs of near-isogenic wheat lines, Chuanmai 28 three pistils (CMTP) and Chinese Spring three pistils (CSTP), were constructed using SSH. A total of 68 clones in CMTP lines and 197 clones in CSTP lines were identified as potentially over-expressed clones. Thirty-two out of 68 clones in CMTP lines belonged to unknown proteins; while, the remaining 30 clones shared homology to diverse classes of genes involved in protein modulation and protein synthesis, signal transduction, and ion transporters. Approximately 67% of genes in CSTP lines were either unclassified or had no matches ('no hits') in the database and about 33% of identified genes encoded polypeptides with known functions. Sequence comparisons of cDNA clones between the two forward cDNA libraries revealed that four genes, encoding thioredoxin H, ubiquitin protein ligases, MCM2, and ubiquinol-cytochrome C reductase complex 14 kDa proteins, were over-expressed in both libraries. These genes would likely play an important role in determining the three pistils trait in the mutant wheat line. [ABSTRACT FROM AUTHOR]