A multi-layered screening method to identify plant regulatory genes
IEEE/ACM Trans. Comput. Biology Bioinform.(2014)
摘要
We used a seven-step process to identify genes involved in glucosinolate biosynthesis and metabolism in the Chinese cabbage (Brassica rapa). We constructed an annotated data set with 34,570 unigenes from B. rapa and predicted 11,526 glucosinolate-related candidate genes using expression profiles generated across nine stages of development on a 47k-gene microarray. Using our multi-layered screening method, we screened 392 transcription factors, 843 pathway genes, and 4,162 ortholog genes associated with glucosinolate-related biosynthesis. Finally, we identified five genes by comparison of the pathway-network genes including the transcription-factor genes and the ortholog-ontology genes. The five genes were anchored to the chromosomes of B. rapa to characterize their genetic-map positions, and phylogenetic reconstruction with homologous genes was performed. These anchored genes were verified by reverse-transcription polymerase chain reaction. While the five genes identified by our multi-layered screen require further characterization and validation, our study demonstrates the power of multi-layered screening after initial identification of genes on microarrays.
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关键词
metabolism,genetic-map positions,medical information systems,design,experimentation,botany,ortholog genes,pathway genes,genes regulating,pathway-network genes,multilayered screening method,transcription-factor genes,genetics,genomics,seven-step process,biology and genetics,expression profiles,glucosinolate-related candidate genes,biochemistry,plant regulatory gene identification,measurement,phylogenetic reconstruction,chromosomes,anchored genes,chinese cabbage,47k-gene microarray,glucosinolate biosynthesis,transcription factor,annotated data set,ontologies (artificial intelligence),ortholog-ontology genes,unigenes,brassica rapa,reverse-transcription polymerase chain reaction,bioinformatics,performance,homologous genes,glucosinolate-related biosynthesis,databases,computational biology,production
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