title: The word landscape of the non-coding segments of the Arabidopsis thaliana genome.
abstract: BACKGROUND
  Genome sequences can be conceptualized as arrangements of motifs or words. The frequencies and positional distributions of these words within particular non-coding genomic segments provide important insights into how the words function in processes such as mRNA stability and regulation of gene expression.
  
  
  RESULTS
  Using an enumerative word discovery approach, we investigated the frequencies and positional distributions of all 65,536 different 8-letter words in the genome of Arabidopsis thaliana. Focusing on promoter regions, introns, and 3' and 5' untranslated regions (3'UTRs and 5'UTRs), we compared word frequencies in these segments to genome-wide frequencies. The statistically interesting words in each segment were clustered with similar words to generate motif logos. We investigated whether words were clustered at particular locations or were distributed randomly within each genomic segment, and we classified the words using gene expression information from public repositories. Finally, we investigated whether particular sets of words appeared together more frequently than others.
  
  
  CONCLUSIONS
  Our studies provide a detailed view of the word composition of several segments of the non-coding portion of the Arabidopsis genome. Each segment contains a unique word-based signature. The respective signatures consist of the sets of enriched words, 'unwords', and word pairs within a segment, as well as the preferential locations and functional classifications for the signature words. Additionally, the positional distributions of enriched words within the segments highlight possible functional elements, and the co-associations of words in promoter regions likely represent the formation of higher order regulatory modules. This work is an important step toward fully cataloguing the functional elements of the Arabidopsis genome.
authors.affiliation: Bioinformatics Laboratory, School of Electrical Engineering and Computer Science, Ohio University, Athens, OH, USA. lichtenj@ohio.edu
authors.forename: Jens
authors.initials: J
authors.lastname: Lichtenberg
authors.forename: Alper
authors.initials: A
authors.lastname: Yilmaz
authors.forename: Joshua D
authors.initials: JD
authors.lastname: Welch
authors.forename: Kyle
authors.initials: K
authors.lastname: Kurz
authors.forename: Xiaoyu
authors.initials: X
authors.lastname: Liang
authors.forename: Frank
authors.initials: F
authors.lastname: Drews
authors.forename: Klaus
authors.initials: K
authors.lastname: Ecker
authors.forename: Stephen S
authors.initials: SS
authors.lastname: Lee
authors.forename: Matt
authors.initials: M
authors.lastname: Geisler
authors.forename: Erich
authors.initials: E
authors.lastname: Grotewold
authors.forename: Lonnie R
authors.initials: LR
authors.lastname: Welch
mesh_terms: D020413:3' Untranslated Regions; D020121:5' Untranslated Regions; D017360:Arabidopsis / Q000235:genetics*; D019295:Computational Biology / Q000379:methods*; D018744:DNA, Plant / Q000235:genetics; D018506:Gene Expression Regulation, Plant; D018745:Genome, Plant; D007438:Introns; D008390:Markov Chains; D015233:Models, Statistical; D011401:Promoter Regions, Genetic; D017422:Sequence Analysis, DNA
chemical_list: D020413:3' Untranslated Regions; D020121:5' Untranslated Regions; D018744:DNA, Plant