Automating Genomic Data Mining via a Sequence-based Matrix Format and Associative Rule Set

There is an enormous amount of information encoded in each genome – enough to create living, responsive and adaptive organisms. Raw sequence data alone is not enough to understand function, mechanisms or interactions. Changes in a single base pair can lead to disease, such as sickle-cell anemia, while some large megabase deletions have no apparent phenotypic effect. Genomic features are varied in their data types and annotation of these features is spread across multiple databases. Herein, we develop a method to automate exploration of genomes by iteratively exploring sequence data for correlations and building upon them. First, to integrate and compare different annotation sources, a sequence matrix (SM) is developed to contain position-dependant information. Second, a classification tree is developed for matrix row types, specifying how each data type is to be treated with respect to other data types for analysis purposes. Third, correlative analyses are developed to analyze features of each matrix row in terms of the other rows, guided by the classification tree as to which analyses are appropriate. A prototype was developed and successful in detecting coinciding genomic features among genes, exons, repetitive elements and CpG islands

Increased expression of carbonic anhydrase I in the synovium of patients with ankylosing spondylitis

<p>Abstract</p> <p>Background</p> <p>One of the most distinctive features of ankylosing spondylitis (AS) is new bone formation and bone resorption at sites of chronic inflammation. Previous studies have indicated that the hyperplasia and inflammation of synovial tissues are significantly related to the pathogenic process of AS. The present study used a proteomic approach to identify novel AS-specific proteins by simultaneously comparing the expression profiles of synovial membranes from patients with AS, rheumatoid arthritis (RA) and osteoarthritis (OA).</p> <p>Methods</p> <p>Synovial tissues were collected from the hip joints of patients with AS and knee joints of patients with RA or OA (n = 10 for each disease) during joint replacement surgery. Proteins extracted from the synovial tissues were separated by 2-D electrophoresis (2-DE), and the proteins with significantly increased expression in the AS samples were subjected to MALDI-TOF/TOF-MS analysis. The results were verified using western blotting and immunohistochemistry. Levels of the candidate proteins in synovial fluids from knee joints (n = 40 for each disease) were measured using ELISA.</p> <p>Results</p> <p>The proteomic approach revealed significantly increased expression of carbonic anhydrase I (CA1) in the synovial membrane of patients with AS as compared with the RA and OA tissue samples. Immunohistochemistry and western blotting analysis confirmed the findings described above. The ELISA detected a higher level of CA1 in synovial fluids from patients with AS than those with OA. The mean value of the CA1 level was also higher in AS patients as compared with RA patients. This study also detected increased expression of alpha-1-antitrypsin in the synovial tissues from AS patients, which is in agreement with other reports.</p> <p>Conclusion</p> <p><it>In vitro </it>experiments by other groups indicated that CA1 catalyzes the generation of HCO₃^-through the hydration of CO₂, which then combines with Ca²⁺to form a CaCO3 precipitate. Calcification is an essential step of bone formation. Substantial evidence indicates that carbonic anhydrase also stimulates bone resorption. Hence, overexpression of CA1 in the synovial tissues of AS patients may promote improper calcification and bone resorption in AS.</p