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Wheat Gene Expression Atlas

We would like to introduce www.wheat-expression.com where you can easily visualise and explore the homoeologue-specific expression patterns of your wheat genes of interest. We have added > 400 publicly available RNA-seq samples to an expression browser which can be dynamically filtered and sorted according to tissue, developmental stage, disease, abiotic stress and variety.

GRIS, Genetic Resources Information System for Wheat and Triticale

The system GRIS contains the passport data for 171 000 varieties and lines (names and synonyms) – accession name, accession number, pedigree, botanical species and variety, growth habit, geographical origin, identified gene alleles, synonym, genetic status, year of registration, originator, recommended region for cultivation, years of use, maturing, market class, milling and baking quality, reaction to biotic and abiotic stressors (resistance/ tolerance/ moderate resistance/ susceptibility), sensitivity/ insensitivity to day length, gibberellic acid etc., morphological traits.

Genome-Specific Primers in Polyploid Species

The sequences among subgenomes in a polyploid species share high similarity. This makes it difficult to design genome-specific primers for sequence analysis. GSP, a web-based platform to design genome-specific primers that distinguish subgenome sequences in the polyploid wheat genome. GSP uses BLAST to extract homeologous sequences of the subgenomes in the existing databases, performs a multiple sequence alignment, and designs primers based on sequence variants in the alignment.

WheatExp : A Tool to Visualize Gene Expression in Wheat

Presented is WheatExp, an expression database and visualization tool to analyze and compare homoeologue-specific transcript profiles across a broad range of tissues from different developmental stages in polyploid wheat. Beginning with publicly-available RNA-seq datasets, a pipeline was developed to distinguish between homoeologous transcripts from each annotated gene in the hexaploid bread wheat genome. We have processed and compiled data from multiple studies into a database which can be queried either by BLAST or by searching for a known gene of interest by name or functional domain.

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