%0 Journal Article
%T ArchAlign: coordinate-free chromatin alignment reveals novel architectures
%A William KM Lai
%A Michael J Buck
%J Genome Biology
%D 2010
%I BioMed Central
%R 10.1186/gb-2010-11-12-r126
%X The development of protein and DNA sequence alignment algorithms in the 1970s and 1980s revolutionized the functional characterization of unknown proteins and genes [1,2]. Since then sequence-based alignments have become so accepted that when a pairwise percentage identity is high enough, a gene or protein is now assigned a function without biochemical confirmation [3]. Similar to the explosion of sequence data in the 1980s, today there is an exponential growth in chromatin structural data. The majority of chromatin data are being generated by next-generation DNA sequencing combined with chromatin immunoprecipitation (ChIP), FAIRE (formaldehyde-assisted isolation of regulatory elements), DNAse I hypersensitivity, or micrococcal nuclease (MNase) digestion assays [4]. Analysis of these high resolution datasets has discovered shared chromatin architectures at previously defined functional elements in the genome; however, identification of new functional elements and their chromatin signatures remains limited.Currently, the only way to characterize chromatin architecture is to have an accurately mapped functional element in the genome. Functional elements include genes for protein and non-coding RNAs, and regulatory sequences that direct essential functions such as gene expression, DNA replication, and chromosome inheritance. With an accurately mapped functional element, chromatin structural data are aligned by the genomic coordinates and an average profile is created. For example, transcription start sites (TSSs) in Saccharomyces cerevisiae have a well documented nucleosome-depleted region approximately 50 to 100 bp upstream of the TSS, flanked by a non-canonical acetylated nucleosome containing the histone variant H2A.Z [5]. Chromatin architecture at these regions was identified because TSSs had been accurately determined through other molecular methods. In addition to TSSs, researchers have used genomic datasets to identify shared chromatin architectures at origins o
%U http://genomebiology.com/2010/11/12/R126