NBLAST: a cluster variant of BLAST for NxN comparisons

Background  

The BLAST algorithm compares biological sequences to one another in order to determine shared motifs and common ancestry. However, the comparison of all non-redundant (NR) sequences against all other NR sequences is a computationally intensive task. We developed NBLAST as a cluster computer implementation of the BLAST family of sequence comparison programs for the purpose of generating pre-computed BLAST alignments and neighbour lists of NR sequences.     

Ultra-deep sequencing of mouse mitochondrial DNA: mutational patterns and their origins

Somatic mutations of mtDNA are implicated in the aging process, but there is no universally accepted method for their accurate quantification. We have used ultra-deep sequencing to study genome-wide mtDNA mutation load in the liver of normally- and prematurely-aging mice. Mice that are homozygous for an allele expressing a proof-reading-deficient mtDNA polymerase (mtDNA mutator mice) have 10-times-higher point mutation loads than their wildtype siblings. In addition, the mtDNA mutator mice have increased levels of a truncated linear mtDNA molecule, resulting in decreased sequence coverage in the deleted region. In contrast, circular mtDNA molecules with large deletions occur at extremely low frequencies in mtDNA mutator mice and can therefore not drive the premature aging phenotype. Sequence analysis shows that the main proportion of the mutation load in heterozygous mtDNA mutator mice and their wildtype siblings is inherited from their heterozygous mothers consistent with germline transmission. We found no increase in levels of point mutations or deletions in wildtype C57Bl/6N mice with increasing age, thus questioning the causative role of these changes in aging. In addition, there was no increased frequency of transversion mutations with time in any of the studied genotypes, arguing against oxidative damage as a major cause of mtDNA mutations. Our results from studies of mice thus indicate that most somatic mtDNA mutations occur as replication errors during development and do not result from damage accumulation in adult life.     

Mitochondrial genomics identifies major haplogroups in Aboriginal Australians

We classified diversity in eight new complete mitochondrial genome sequences and 41 partial sequences from living Aboriginal Australians into five haplogroups. Haplogroup AuB belongs to global lineage M, and AuA, AuC, AuD, and AuE to N. Within N, we recognize subdivisions, assigning AuA to haplogroup S, AuD to haplogroup O, AuC to P4, and AuE to P8. On available evidence, (S)AuA and (M)AuB are widespread in Australia. (P4)AuC is found in the Riverine region of western New South Wales, and was identified by others in northern Australia. (O)AuD and (P8)AuE were clearly identified only from central Australia. Our eight Australian full mt genome sequences, combined with 20 others (Ingman and Gyllensten 2003 Genome Res. 13:1600-1606) and compared with full mt genome sequences from regions to the north that include Papua New Guinea, Malaya, and Andaman and Nicobar Islands, show that ancestral connections between regions are deep and limited to clustering at the level of the N and M macrohaplogroups. The Australian-specific distribution of the five haplogroups identified indicates genetic isolation over a long period. Ancestral connections within Australia are deeper than those reflected by known linguistic or culturally based affinities. Applying a coalescence analysis to a gene tree for the coding regions of the eight genomic sequences, we made estimates of time depth that support a continuity of presence for the descendants of a founding population already established by 40,000 years ago.     

PreBIND and Textomy – mining the biomedical literature for protein-protein interactions using a support vector machine

Background

The majority of experimentally verified molecular interaction and biological pathway data are present in the unstructured text of biomedical journal articles where they are inaccessible to computational methods. The Biomolecular interaction network database (BIND) seeks to capture these data in a machine-readable format. We hypothesized that the formidable task-size of backfilling the database could be reduced by using Support Vector Machine technology to first locate interaction information in the literature. We present an information extraction system that was designed to locate protein-protein interaction data in the literature and present these data to curators and the public for review and entry into BIND.

Results

Cross-validation estimated the support vector machine's test-set precision, accuracy and recall for classifying abstracts describing interaction information was 92%, 90% and 92% respectively. We estimated that the system would be able to recall up to 60% of all non-high throughput interactions present in another yeast-protein interaction database. Finally, this system was applied to a real-world curation problem and its use was found to reduce the task duration by 70% thus saving 176 days.

Conclusions

Machine learning methods are useful as tools to direct interaction and pathway database back-filling; however, this potential can only be realized if these techniques are coupled with human review and entry into a factual database such as BIND. The PreBIND system described here is available to the public at http://bind.ca. Current capabilities allow searching for human, mouse and yeast protein-interaction information.     

An automated method for finding molecular complexes in large protein interaction networks

Background  

Recent advances in proteomics technologies such as two-hybrid, phage display and mass spectrometry have enabled us to create a detailed map of biomolecular interaction networks. Initial mapping efforts have already produced a wealth of data. As the size of the interaction set increases, databases and computational methods will be required to store, visualize and analyze the information in order to effectively aid in knowledge discovery.     

Domain-based small molecule binding site annotation

Background  

Accurate small molecule binding site information for a protein can facilitate studies in drug docking, drug discovery and function prediction, but small molecule binding site protein sequence annotation is sparse. The Small Molecule Interaction Database (SMID), a database of protein domain-small molecule interactions, was created using structural data from the Protein Data Bank (PDB). More importantly it provides a means to predict small molecule binding sites on proteins with a known or unknown structure and unlike prior approaches, removes large numbers of false positive hits arising from transitive alignment errors, non-biologically significant small molecules and crystallographic conditions that overpredict ion binding sites.     

Polymorphisms in 9q32 and <Emphasis Type="Italic">TSCOT</Emphasis> are linked to cervical cancer in affected sib-pairs with high mean age at diagnosis

Cervical cancer is a multifactorial disease influenced by both environmental and genetic factors. We have previously found linkage to 9q32 in a genomewide scan of affected sib-pairs (ASPs) with cervical cancer and to the thymic stromal co-transporter (TSCOT), a candidate gene in this region. Here we examined the contribution of 9q32 and TSCOT to cervical cancer susceptibility using at larger material of 641 ASPs, 278 of which were included in the earlier genome-scan. Since heritable forms of cancer frequently show stronger genetic effects in families with early onset of disease, we stratified the ASPs into two groups based on mean age at diagnosis (MAAD) within sib-pairs. Surprisingly, ASPs with high MAAD (30.5–47.5 years) showed increased sharing at all microsatellite markers at 9q31.1–33.1 and linkage signals of up to MLS = 2.74 for TSCOT SNPs, while ASPs with low MAAD (19–30 years) showed no deviation from random genetic sharing (MLS = 0.00). The difference in allelic sharing between the two MAAD strata was significant (P < 0.005) and is not likely to be explained by the HLA haplotype, a previously known genetic susceptibility factor for cervical cancer. Our results indicate locus heterogeneity in the susceptibility to cervical cancer between the two strata, with polymorphisms in the 9q32 region mainly showing an effect in women with high MAAD.     

Microhabitat use by white-footed mice Peromyscus leucopus in forested and old-field habitats occupied by Morrow's honeysuckle Lonicera morrowii

We quantified microhabitat use by white-footed mice Peromyscus leucopus in forest and old-field habitats occupied by Morrow's honeysuckle Lonicera morrowii, an invasive exotic shrub imported from Japan. Microhabitat characteristics were compared between trails used by mice (n=124) and randomly selected trails (n=127) in 4 study plots located at Fort Necessity National Battlefield, Farmington, Pennsylvania, USA. We compared 10 microhabitat variables between used and random trails using non-metric multidimensional scaling (NMDS) and classification and regression tree (CART) analysis. Trails used by mice were statistically different from randomly selected trails in both forested plots (P<0.008) and old-field plots (P<0.001). In the forested plots, trails of white-footed mice were more often associated with a greater percent cover (% cover) of coarse woody debris (CWD) than were randomly selected trails. In the old-field plots, mouse trails were commonly characterized by having a lower % cover of exotic herbaceous vegetation, a greater % cover of shrubs, and a greater % cover of Morrow's honeysuckle than randomly selected trails. Our study indicates that white-footed mice do not move randomly and prefer areas of high structural complexity, thereby showing significant microhabitat preference. The preference of white-footed mice for areas with a relatively high percent cover of Morrow's honeysuckle could 1) be a factor in the aggressive nature of the exotic honeysuckle shrub's spread throughout the Battlefield or 2) cause the shrub to spread even faster into adjacent areas not yet occupied by Morrow's honeysuckle[Current Zoology 55(2):111-122,2009].