Arbuscular mycorrhizal symbiosis is a beneficial association between plant roots and fungi that occurs in approximately 80 % of terrestrial plants and which confers different benefits including mineral nutrient acquisition and enhanced defense capacity. Although mycorrhizal colonization takes place in roots, the symbiosis establishment has systemic effects in other parts of the plant, in processes such as nutrient translocation and systemic resistance. In order to understand the transcriptional changes that occur in leaves of mycorrhizal plants, we used RNA-seq technology to obtain the transcriptomes of leaves from mycorrhizal and nonmycorrhizal tomato plants (Solanum lycopersicum). Four weeks after inoculation with the fungus Rhizophagus irregularis, leaves from mycorrhizal and non-mycorrhizal tomato plants were used for transcriptome sequencing. Of the 21,113 genes expressed in tomato leaves, 742 genes displayed differential expression between the mycorrhizal and nonmycorrhizal conditions. Most of the transcriptional changes occurred in the Bprotein,^BRNA,^Bsignaling,^Btransport,^B biotic and abiotic stresses,^and Bhormone metabolism^categories. Some transcriptional changes also occurred in P, N, and sugar transporters, as would be expected for mycorrhizal colonization. Finally, several differentially expressed genes may be related to systemic defense priming, in agreement with our demonstration that symbiotic plants exhibited mycorrhizainduced resistance against the foliar pathogen Xanthomonas campestris pv. vesicatoria. This is the first study to take on a genome-wide analysis aimed at understanding the expression changes in leaves of mycorrhiza-colonized plants. The results will therefore be valuable to future analyses focused on specific genes, as well as detailed studies of the expression profiles of certain gene families.

We present a new algorithm to determine, quickly and accurately, the best-in-focus image of biological particles. The algorithm is based on a one-dimensional Fourier transform and on the Pearson correlation for automated microscopes along the Z axis. We captured a set of several images at different Z distances from a biological sample. The algorithm uses the Fourier transform to obtain and extract the image frequency content of a vector pattern previously specified to be sought in each captured image; comparing these frequency vectors with the frequency vector of a reference image (usually the first image that we capture or the most out-of-focus image), we find the best-in-focus image via the Pearson correlation. Numerical experimental results show the algorithm has a fast response for finding the best-in-focus image among the captured images, compared with related autofocus techniques presented in the past. The algorithm can be implemented in real-time systems with fast response, accuracy, and robustness; it can be used to get focused images in bright and dark fields; and it offers the prospect of being extended to include fusion techniques to construct multifocus final images.

To explore gonad‐specific gene transcription in the red abalone Haliotis rufescens, cDNA from mature reproductive tissues was 454‐pyrosequenced. A total of 79 877 and 133 850 high‐quality reads were generated for females and males, respectively, with an average length of 600 bp. Clustering and assembly of these reads produced a non‐redundant set of unique sequences, comprising 2793 and 10 354 contigs, 8581 and 32 175 singletons, respectively, for males and females. In silico gene transcription analysis, comparing the sexes showed that 20% of the differentially expressed transcripts are involved in sex‐specific patterns. Gene ontology analysis revealed a higher percentage of metabolic processes associated with females, whereas binding processes and biological regulation were mainly related to male transcriptomes. Single nucleotide polymorphism (SNP) associated with sex‐related genes, such as lysin (SNP102), PF (SNP1254) and VTG (SNP876) were discovered and validated through high‐resolution melting analysis. This study generated relevant genomic sequence data that might contribute to a better understanding of the various reproductive biological processes occurring in abalone. Once the underlying biological processes are understood, biotechnological methods to control maturation, identify sex and produce monosex lines for abalone aquaculture can be envisioned.

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We present a nonlinear correlation methodology to recognize objects. This system is invariant to position, rotation, and scale by using vectorial signatures obtained from the target such as those from problem images. Vectorial signatures are calculated through several mathematical transformations such as scale and Fourier transform. In this application, vectorial signatures are compared using nonlinear correlations. Also, experiments were carried out in order to find the noise tolerance. The discrimination coefficient was used as a metric in performance evaluation in presence of noise. In addition, spectral index and vectorial signature index are obtained in order to recognize objects in a simpler way. This technique has low computational cost. The invariance to position, rotation, and scale digital system was tested with 21 different fossil diatoms images. The results obtained are good, and the confidence level is above 95.4%.