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Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/62527/1/417588b.pd

Sequence Assembly Validation by Restriction Digest Fingerprint Comparison

DNA sequence analysis depends on the accurate assembly of fragment reads for the determination of a consensus sequence. Genomic sequences frequently contain repeat elements that may confound the fragment assembly process, and errors in fragment assembly, and errors in fragment assembly may seriously impact the biological interpretation of the sequence data. Validating the fidelity of sequence assembly by experimental means is desirable. This report examines the use of restriction digest analysis as a method for testing the fidelity of sequence assembly. Restriction digest fingerprint matching is an established technology for high resolution physical map construction, but the requirements for assembly validation differ from those of fingerprint mapping. Fingerprint matching is a statistical process that is robust to the presence of errors in the data and independent of absolute fragment mass determination. Assembly validation depends on the recognition of a small number of discrepant fragments and is very sensitive to both false positive and false negative errors in the data. Assembly validation relies on the comparison of absolute masses derived from sequence with masses that are experimenally determined, making absolute accuracy as well as experimental precision important. As the size of a sequencing project increases, the difficulties in assembly validation by restriction fingerprinting befcome more severe. Simulation studies are used to demonstrate that large-scale errors in sequence assembly can escape detection in fingerprint pattern comparison. Alternative technologies for sequence assembly validation are discussed

Assembly and Analysis of Extended Human Genomic Contig Regions

The Human Genome Project (HGP) has led to the deposit of human genomic sequence in the form of sequenced clones into various databases such as the DNA Data Bank of Japan (DDBJ) (Tateno and Gojobori, 1997), the European Molecular Biology Laboratory (EMBL) Nucleotide Sequence Database (Stoesser, et. al., 1999), and GenBank (Benson, et. al., 1998). Many of these sequenced clones occur in regions where sequencing has taken place either within the same sequencing center or other centers throughout the world. The assembly of extended segments of genomic sequence by looking at overlapping end segments is desired and is currently availabel only in a limited sense from the National Center for Biotechnology Information (NCBI) (http://www.ncbi.nlm.nih.gov/genome/seq/) and Oak Ridge National Laboratories\u27 (ORNL) Genome Channel (http://compbio.ornl.gov/tools/channel/). We attempt to collate a definitive set of nonredundant extended segments of human genomic sequence by taking individual human entires in GenBank greater than 25 kilobases (kb) and extending them on either end. We address the several difficulties that arise when attempting to extend segments

Compositional Analysis of Homogeneous Regions in Human Genomic DNA

Due to increased production of human DNA sequence, it is now possible to explore and understand human genomic organization at the sequence level. In particular, we have studied one of the major organizational components of vertebrate genome organization previously described as isochores (Bernardi, 1993), which are compositionally homogeneous DNA segments based on G+C content. We have examined sequence data for the existence of compositionally differing regions and report that while compositionally homogeneous regions are present in the human genome, current isochore classification schemes are too brad for sequence-level data

Computational Detection of CpG Islands in DNA

Regions of DNA rich in CpG dinucleotides, also known as CpG islands, are often located upstream of the transcription start side in both tissue specific and housekeeping genes. Overall, CPG dinucleotides are observed at a density of 25% the expected level from base composition alone, partially due to 5-methylcytosine decay (Bird, 1993). Since CpG dinucleotides typically occur with low frequency, CpG islands can be distinguished statistically in the genome. Our method of detecting CpG islands involves a heuristic algorithm employing classic changepoint methods and log-likelihood statistics. A Java applet has been created to allow for user interaction and visualization of the segmentation resulting from the changepoint analysis. The model is tested using several sequences obtainable from GenBank (NCBI, 1997), including a 220 Kb fragment of human X chromosome from the filanin (FLM) gene to the glucose-6-phosphate dehydrogenase (G6PD) gene which has been experimentally studied (Rivella, et. al., 1995; E.Y. Chen, et. all., 1996). Preliminary results suggest a breakpoint segmentation that is consistent with observable manual analysis. About 56% of human genes have associated CpG rich islands (Antequera and Bird, 1993). By identifying the CpG islands, it is thought that regions of DNA coding for housekeeping or tissue-specific genes can be located (Antequera and Bird, 1993) even in the absence of transcriptional activity. Biological experiments searching for such genes can then be narrowed given the locations of the CpG islands

Motif Discovery in Tissue-Specific Regulatory Sequences Using Directed Information

Motif discovery for the identification of functional regulatory elements underlying gene expression is a challenging problem. Sequence inspection often leads to discovery of novel motifs (including transcription factor sites) with previously uncharacterized function in gene expression. Coupled with the complexity underlying tissue-specific gene expression, there are several motifs that are putatively responsible for expression in a certain cell type. This has important implications in understanding fundamental biological processes such as development and disease progression. In this work, we present an approach to the identification of motifs (not necessarily transcription factor sites) and examine its application to some questions in current bioinformatics research. These motifs are seen to discriminate tissue-specific gene promoter or regulatory regions from those that are not tissue-specific. There are two main contributions of this work. Firstly, we propose the use of directed information for such classification constrained motif discovery, and then use the selected features with a support vector machine (SVM) classifier to find the tissue specificity of any sequence of interest. Such analysis yields several novel interesting motifs that merit further experimental characterization. Furthermore, this approach leads to a principled framework for the prospective examination of any chosen motif to be discriminatory motif for a group of coexpressed/coregulated genes, thereby integrating sequence and expression perspectives. We hypothesize that the discovery of these motifs would enable the large-scale investigation for the tissue-specific regulatory role of any conserved sequence element identified from genome-wide studies