Using The <i>Arabidopsis</i> Information Resource (TAIR) to Find Information About <i>Arabidopsis</i> Genes

Lamesch, Philippe; Dreher, Kate; Swarbreck, David; Sasidharan, Rajkumar; Reiser, Leonore; Huala, Eva

doi:10.1002/0471250953.bi0111s30

Cited by 38 publications

(38 citation statements)

References 40 publications

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“…The raw data were first aligned to the So0157-2 genome. Removal of rRNA and tRNA sequences was conducted with Bowtie 249. RNA-Seq reads were aligned to the reference genome using the Burrows-Wheeler Aligner50.…”

Section: Methodsmentioning

confidence: 99%

Extraordinary expansion of a Sorangium cellulosum genome from an alkaline milieu

Han

Peng

et al. 2013

Sci Rep

114

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Complex environmental conditions can significantly affect bacterial genome size by unknown mechanisms. The So0157-2 strain of Sorangium cellulosum is an alkaline-adaptive epothilone producer that grows across a wide pH range. Here, we show that the genome of this strain is 14,782,125 base pairs, 1.75-megabases larger than the largest bacterial genome from S. cellulosum reported previously. The total 11,599 coding sequences (CDSs) include massive duplications and horizontally transferred genes, regulated by lots of protein kinases, sigma factors and related transcriptional regulation co-factors, providing the So0157-2 strain abundant resources and flexibility for ecological adaptation. The comparative transcriptomics approach, which detected 90.7% of the total CDSs, not only demonstrates complex expression patterns under varying environmental conditions but also suggests an alkaline-improved pathway of the insertion and duplication, which has been genetically testified, in this strain. These results provide insights into and a paradigm for how environmental conditions can affect bacterial genome expansion.

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Section: Methodsmentioning

confidence: 99%

Extraordinary expansion of a Sorangium cellulosum genome from an alkaline milieu

Han

Peng

et al. 2013

Sci Rep

114

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“…To analyze functional annotation for each transcript, we aligned contig and singlet sequences with a lower expect value of 1e -10 against plant non-redundant (NR) proteins downloaded from the NCBI database [75] and against Arabidopsis proteins downloaded from TAIR (ver. 10; http://www.arabidopsis.org/) [76]. Based on the Arabidopsis annotation, we integrated pathway information referring to KEGG [77], FunCat [78], and plant ontology (PO) [79,80].…”

Section: Methodsmentioning

confidence: 99%

Small RNA and transcriptome deep sequencing proffers insight into floral gene regulation in Rosa cultivars

Kim

Park

Lim³

et al. 2012

BMC Genomics

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BackgroundRoses (Rosa sp.), which belong to the family Rosaceae, are the most economically important ornamental plants—making up 30% of the floriculture market. However, given high demand for roses, rose breeding programs are limited in molecular resources which can greatly enhance and speed breeding efforts. A better understanding of important genes that contribute to important floral development and desired phenotypes will lead to improved rose cultivars. For this study, we analyzed rose miRNAs and the rose flower transcriptome in order to generate a database to expound upon current knowledge regarding regulation of important floral characteristics. A rose genetic database will enable comprehensive analysis of gene expression and regulation via miRNA among different Rosa cultivars.ResultsWe produced more than 0.5 million reads from expressed sequences, totalling more than 110 million bp. From these, we generated 35,657, 31,434, 34,725, and 39,722 flower unigenes from Rosa hybrid: ‘Vital’, ‘Maroussia’, and ‘Sympathy’ and Rosa rugosa Thunb. , respectively. The unigenes were assigned functional annotations, domains, metabolic pathways, Gene Ontology (GO) terms, Plant Ontology (PO) terms, and MIPS Functional Catalogue (FunCat) terms. Rose flower transcripts were compared with genes from whole genome sequences of Rosaceae members (apple, strawberry, and peach) and grape. We also produced approximately 40 million small RNA reads from flower tissue for Rosa, representing 267 unique miRNA tags. Among identified miRNAs, 25 of them were novel and 242 of them were conserved miRNAs. Statistical analyses of miRNA profiles revealed both shared and species-specific miRNAs, which presumably effect flower development and phenotypes.ConclusionsIn this study, we constructed a Rose miRNA and transcriptome database, and we analyzed the miRNAs and transcriptome generated from the flower tissues of four Rosa cultivars. The database provides a comprehensive genetic resource which can be used to better understand rose flower development and to identify candidate genes for important phenotypes.

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“…The spelling correction algorithm of Section 3.3 was benchmarked using 5,401 pairs of spelling corrected words [22]. To create this benchmark set we analysed a one-year query log of the TAIR database [23] a comprehensive information system for the genome of the model plant Arabidopsis thaliana. We assumed that the last query in a session is the correct one from a user's perspective.…”

Section: Resultsmentioning

confidence: 99%

A Query Suggestion Workflow for Life Science IR-Systems

Esch

Chen

Weise

et al. 2014

Journal of Integrative Bioinformatics

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SummaryInformation Retrieval (IR) plays a central role in the exploration and interpretation of integrated biological datasets that represent the heterogeneous ecosystem of life sciences. Here, keyword based query systems are popular user interfaces. In turn, to a large extend, the used query phrases determine the quality of the search result and the effort a scientist has to invest for query refinement. In this context, computer aided query expansion and suggestion is one of the most challenging tasks for life science information systems. Existing query front-ends support aspects like spelling correction, query refinement or query expansion. However, the majority of the front-ends only make limited use of enhanced IR algorithms to implement comprehensive and computer aided query refinement workflows. In this work, we present the design of a multi-stage query suggestion workflow and its implementation in the life science IR system LAILAPS. The presented workflow includes enhanced tokenisation, word breaking, spelling correction, query expansion and query suggestion ranking. A spelling correction benchmark with 5,401 queries and manually selected use cases for query expansion demonstrate the performance of the implemented workflow and its advantages compared with state-of-the-art systems.

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Using The Arabidopsis Information Resource (TAIR) to Find Information About Arabidopsis Genes

Cited by 38 publications

References 40 publications

Extraordinary expansion of a Sorangium cellulosum genome from an alkaline milieu

Extraordinary expansion of a Sorangium cellulosum genome from an alkaline milieu

Small RNA and transcriptome deep sequencing proffers insight into floral gene regulation in Rosa cultivars

A Query Suggestion Workflow for Life Science IR-Systems

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