CiteULike: indigoviolet's Eisen

Benchmarking tools for the alignment of functional noncoding DNA.

DA Pollard — 2006-08-03T00:32:10-00:00

BMC Bioinformatics, Vol. 5 (21 January 2004)

BACKGROUND: Numerous tools have been developed to align genomic sequences. However, their relative performance in specific applications remains poorly characterized. Alignments of protein-coding sequences typically have been benchmarked against "correct" alignments inferred from structural data. For noncoding sequences, where such independent validation is lacking, simulation provides an effective means to generate "correct" alignments with which to benchmark alignment tools. RESULTS: Using rates of noncoding sequence evolution estimated from the genus Drosophila, we simulated alignments over a range of divergence times under varying models incorporating point substitution, insertion/deletion events, and short blocks of constrained sequences such as those found in cis-regulatory regions. We then compared "correct" alignments generated by a modified version of the ROSE simulation platform to alignments of the simulated derived sequences produced by eight pairwise alignment tools (Avid, BlastZ, Chaos, ClustalW, DiAlign, Lagan, Needle, and WABA) to determine the off-the-shelf performance of each tool. As expected, the ability to align noncoding sequences accurately decreases with increasing divergence for all tools, and declines faster in the presence of insertion/deletion evolution. Global alignment tools (Avid, ClustalW, Lagan, and Needle) typically have higher sensitivity over entire noncoding sequences as well as in constrained sequences. Local tools (BlastZ, Chaos, and WABA) have lower overall sensitivity as a consequence of incomplete coverage, but have high specificity to detect constrained sequences as well as high sensitivity within the subset of sequences they align. Tools such as DiAlign, which generate both local and global outputs, produce alignments of constrained sequences with both high sensitivity and specificity for divergence distances in the range of 1.25-3.0 substitutions per site. CONCLUSION: For species with genomic properties similar to Drosophila, we conclude that a single pair of optimally diverged species analyzed with a high performance alignment tool can yield accurate and specific alignments of functionally constrained noncoding sequences. Further algorithm development, optimization of alignment parameters, and benchmarking studies will be necessary to extract the maximal biological information from alignments of functional noncoding DNA.

Exploiting transcription factor binding site clustering to identify cis-regulatory modules involved in pattern formation in the Drosophila genome.

BP Berman — 2007-09-17T19:14:17-00:00

Proc Natl Acad Sci U S A, Vol. 99, No. 2. (22 January 2002), pp. 757-762.

A major challenge in interpreting genome sequences is understanding how the genome encodes the information that specifies when and where a gene will be expressed. The first step in this process is the identification of regions of the genome that contain regulatory information. In higher eukaryotes, this cis-regulatory information is organized into modular units [cis-regulatory modules (CRMs)] of a few hundred base pairs. A common feature of these cis-regulatory modules is the presence of multiple binding sites for multiple transcription factors. Here, we evaluate the extent to which the tendency for transcription factor binding sites to be clustered can be used as the basis for the computational identification of cis-regulatory modules. By using published DNA binding specificity data for five transcription factors active in the early Drosophila embryo, we identified genomic regions containing unusually high concentrations of predicted binding sites for these factors. A significant fraction of these binding site clusters overlap known CRMs that are regulated by these factors. In addition, many of the remaining clusters are adjacent to genes expressed in a pattern characteristic of genes regulated by these factors. We tested one of the newly identified clusters, mapping upstream of the gap gene giant (gt), and show that it acts as an enhancer that recapitulates the posterior expression pattern of gt.

3D morphology and gene expression in the Drosophila blastoderm at cellular resolution I: data acquisition pipeline

Cris — 2006-12-21T23:16:13-00:00

Genome Biology, Vol. 7 (21 December 2006), R123.

Primate-Specific Evolution of an LDLR Enhancer

Qian-Fei Wang — 2006-08-02T23:11:27-00:00

Genome Biology, Vol. 7 (02 August 2006), R68.

MONKEY: identifying conserved transcription-factor binding sites in multiple alignments using a binding site-specific evolutionary model.

AM Moses — 2005-11-13T03:09:24-00:00

Genome Biol, Vol. 5, No. 12. (2004)

We introduce a method (MONKEY) to identify conserved transcription-factor binding sites in multispecies alignments. MONKEY employs probabilistic models of factor specificity and binding-site evolution, on which basis we compute the likelihood that putative sites are conserved and assign statistical significance to each hit. Using genomes from the genus Saccharomyces, we illustrate how the significance of real sites increases with evolutionary distance and explore the relationship between conservation and function.

Computational identification of developmental enhancers: conservation and function of transcription factor binding-site clusters in Drosophila melanogaster and Drosophila pseudoobscura.

BP Berman — 2004-11-22T00:17:30-00:00

Genome Biol, Vol. 5, No. 9. (2004)

BACKGROUND: The identification of sequences that control transcription in metazoans is a major goal of genome analysis. In a previous study, we demonstrated that searching for clusters of predicted transcription factor binding sites could discover active regulatory sequences, and identified 37 regions of the Drosophila melanogaster genome with high densities of predicted binding sites for five transcription factors involved in anterior-posterior embryonic patterning. Nine of these clusters overlapped known enhancers. Here, we report the results of in vivo functional analysis of 27 remaining clusters. RESULTS: We generated transgenic flies carrying each cluster attached to a basal promoter and reporter gene, and assayed embryos for reporter gene expression. Six clusters are enhancers of adjacent genes: giant, fushi tarazu, odd-skipped, nubbin, squeeze and pdm2; three drive expression in patterns unrelated to those of neighboring genes; the remaining 18 do not appear to have enhancer activity. We used the Drosophila pseudoobscura genome to compare patterns of evolution in and around the 15 positive and 18 false-positive predictions. Although conservation of primary sequence cannot distinguish true from false positives, conservation of binding-site clustering accurately discriminates functional binding-site clusters from those with no function. We incorporated conservation of binding-site clustering into a new genome-wide enhancer screen, and predict several hundred new regulatory sequences, including 85 adjacent to genes with embryonic patterns. CONCLUSIONS: Measuring conservation of sequence features closely linked to function--such as binding-site clusterin--makes better use of comparative sequence data than commonly used methods that examine only sequence identity.