Bioinformatic analysis of expressed sequence tags derived from a compatible Alternaria brassicicola-Brassica oleracea interaction.

SUMMARY Alternaria brassicicola is a necrotrophic fungal pathogen that causes black spot disease on members of the Brassicaceae plant family. In order to identify candidate fungal pathogenicity genes and characterize a compatible host response, a suppression subtractive hybridization (SSH) cDNA library enriched for A. brassicicola and Brassica oleracea genes expressed during the interaction was created, along with a fungal cDNA library representing genes expressed during nitrogen starvation (NS). A total of 3749 and 2352 expressed sequence tags (ESTs) were assembled into 2834 and 1264 unisequence sets for the SSH and NS libraries, respectively. We compared two methods to identify the origins (plant vs. fungal) of ESTs in the SSH library using different classification procedures, with and without the availability of a database representing the A. brassicicola whole genome sequence and Brassicaceae-specific genes. BLASTX analyses of the 2834 unisequence set using the GenBank non-redundant database identified 114 fungal genes. Further BLASTN analyses of the genes with unidentifiable origin using a database consisting of the 1264 fungal unisequence set from the nitrogen-starved library identified 94 additional fungal genes. By contrast, BLASTN analyses of the same SSH unisequence set using a partially assembled A. brassicicola whole genome draft sequence identified a total of 310 unisequenes of fungal origin. Our results indicated that even a small number of organism-specific EST sequences can be very helpful to identify pathogen genes in a library derived from infected tissue, partially overcoming the limitation of the public databases for little studied organisms. However, using the whole genome draft sequence of A. brassicicola we were able to identify approximately 30% more fungal genes in the SSH library than without utilizing this resource. The putative role of specific fungal and plant genes identified in this study in a compatible interaction is discussed.

Group 3 chromosome bin maps of wheat and their relationship to rice chromosome 1.

The focus of this study was to analyze the content, distribution, and comparative genome relationships of 996 chromosome bin-mapped expressed sequence tags (ESTs) accounting for 2266 restriction fragments (loci) on the homoeologous group 3 chromosomes of hexaploid wheat (Triticum aestivum L.). Of these loci, 634, 884, and 748 were mapped on chromosomes 3A, 3B, and 3D, respectively. The individual chromosome bin maps revealed bins with a high density of mapped ESTs in the distal region and bins of low density in the proximal region of the chromosome arms, with the exception of 3DS and 3DL. These distributions were more localized on the higher-resolution group 3 consensus map with intermediate regions of high-mapped-EST density on both chromosome arms. Gene ontology (GO) classification of mapped ESTs was not significantly different for homoeologous group 3 chromosomes compared to the other groups. A combined analysis of the individual bin maps using 537 of the mapped ESTs revealed rearrangements between the group 3 chromosomes. Approximately 232 (44%) of the consensus mapped ESTs matched sequences on rice chromosome 1 and revealed large- and small-scale differences in gene order. Of the group 3 mapped EST unigenes approximately 21 and 32% matched the Arabidopsis coding regions and proteins, respectively, but no chromosome-level gene order conservation was detected.

A 2500-locus bin map of wheat homoeologous group 5 provides insights on gene distribution and colinearity with rice.

We constructed high-density deletion bin maps of wheat chromosomes 5A, 5B, and 5D, including 2338 loci mapped with 1052 EST probes and 217 previously mapped loci (total 2555 loci). This information was combined to construct a consensus chromosome bin map of group 5 including 24 bins. A relatively higher number of loci were mapped on chromosome 5B (38%) compared to 5A (34%) and 5D (28%). Differences in the levels of polymorphism among the three chromosomes were partially responsible for these differences. A higher number of duplicated loci was found on chromosome 5B (42%). Three times more loci were mapped on the long arms than on the short arms, and a significantly higher number of probes, loci, and duplicated loci were mapped on the distal halves than on the proximal halves of the chromosome arms. Good overall colinearity was observed among the three homoeologous group 5 chromosomes, except for the previously known 5AL/4AL translocation and a putative small pericentric inversion in chromosome 5A. Statistically significant colinearity was observed between low-copy-number ESTs from wheat homoeologous group 5 and rice chromosomes 12 (88 ESTs), 9 (72 ESTs), and 3 (84 ESTs).

A chromosome bin map of 16,000 expressed sequence tag loci and distribution of genes among the three genomes of polyploid wheat.

Because of the huge size of the common wheat (Triticum aestivum L., 2n = 6x = 42, AABBDD) genome of 17,300 Mb, sequencing and mapping of the expressed portion is a logical first step for gene discovery. Here we report mapping of 7104 expressed sequence tag (EST) unigenes by Southern hybridization into a chromosome bin map using a set of wheat aneuploids and deletion stocks. Each EST detected a mean of 4.8 restriction fragments and 2.8 loci. More loci were mapped in the B genome (5774) than in the A (5173) or D (5146) genomes. The EST density was significantly higher for the D genome than for the A or B. In general, EST density increased relative to the physical distance from the centromere. The majority of EST-dense regions are in the distal parts of chromosomes. Most of the agronomically important genes are located in EST-dense regions. The chromosome bin map of ESTs is a unique resource for SNP analysis, comparative mapping, structural and functional analysis, and polyploid evolution, as well as providing a framework for constructing a sequence-ready, BAC-contig map of the wheat genome.

Parameter estimation in a model for multidimensional recording of neuronal data: a Gibbsian approximation approach.

This article proposes improved numerical procedures for estimating parameters in a spatiotemporal lattice model introduced for the analysis of cortical activities monitored from arrays of diodes. The numerical algorithms are based on approximations inspired by statistical physics. Both Gibbsian and mean-field approximations are used; they allow for computing local conditional probabilities inside the lattice. The statistical procedures rely on the computation of pseudomaximum-likelihood estimators. The estimators are evaluated on the basis of Monte Carlo simulations. These simulations show that mean-field approximations are useful for reducing the variance of estimators when the data are recorded from arrays of 144 diodes (which are in accordance with standard practice). In light of these improved methods, we give new interpretations for a data set obtained from optical recording of a Guinea pig's auditory cortex in response to pure tone stimulations.