ABSTRACT
Despite the central role of amyloid deposition in the development of Alzheimer's disease (AD), the pathogenesis of AD still remains elusive at the molecular level. Increasing evidence suggests that compromised mitochondrial function contributes to the aging process and thus may increase the risk of AD. Dysfunctional mitochondria contribute to reactive oxygen species (ROS) which can lead to extensive macromolecule oxidative damage and the progression of amyloid pathology. Oxidative stress and amyloid toxicity leave neurons chemically vulnerable. Because the brain relies on aerobic metabolism, it is apparent that mitochondria are critical for the cerebral function. Mitochondrial DNA sequence changes could shift cell dynamics and facilitate neuronal vulnerability. Therefore we postulated that mitochondrial DNA sequence polymorphisms may increase the risk of AD. We evaluated the role of mitochondrial haplogroups derived from 138 mitochondrial polymorphisms in 358 Caucasian Alzheimer's Disease Neuroimaging Initiative (ADNI) subjects. Our results indicate that the mitochondrial haplogroup UK may confer genetic susceptibility to AD independently of the apolipoprotein E4 (APOE4) allele.
Subject(s)
Alzheimer Disease/genetics , DNA, Mitochondrial/genetics , Genetic Variation/genetics , Aged , Aged, 80 and over , Alzheimer Disease/diagnosis , Case-Control Studies , Cohort Studies , Female , Follow-Up Studies , Genes, Mitochondrial/genetics , Genetic Association Studies/methods , Humans , Longitudinal Studies , Male , Phylogeny , Polymorphism, Single Nucleotide/genetics , Prospective Studies , Random AllocationABSTRACT
MOTIVATION: The continuing exponential accumulation of full genome data, including full diploid human genomes, creates new challenges not only for understanding genomic structure, function and evolution, but also for the storage, navigation and privacy of genomic data. Here, we develop data structures and algorithms for the efficient storage of genomic and other sequence data that may also facilitate querying and protecting the data. RESULTS: The general idea is to encode only the differences between a genome sequence and a reference sequence, using absolute or relative coordinates for the location of the differences. These locations and the corresponding differential variants can be encoded into binary strings using various entropy coding methods, from fixed codes such as Golomb and Elias codes, to variables codes, such as Huffman codes. We demonstrate the approach and various tradeoffs using highly variables human mitochondrial genome sequences as a testbed. With only a partial level of optimization, 3615 genome sequences occupying 56 MB in GenBank are compressed down to only 167 KB, achieving a 345-fold compression rate, using the revised Cambridge Reference Sequence as the reference sequence. Using the consensus sequence as the reference sequence, the data can be stored using only 133 KB, corresponding to a 433-fold level of compression, roughly a 23% improvement. Extensions to nuclear genomes and high-throughput sequencing data are discussed. AVAILABILITY: Data are publicly available from GenBank, the HapMap web site, and the MITOMAP database. Supplementary materials with additional results, statistics, and software implementations are available from http://mammag.web.uci.edu/bin/view/Mitowiki/ProjectDNACompression.
Subject(s)
Algorithms , Data Compression/methods , Genomics/methods , Genome , Humans , Sequence Analysis, DNA/methodsABSTRACT
We have developed a computer system, MITOMASTER, to make analysis of human mitochondrial DNA (mtDNA) sequences efficient, accurate, and easily available. From imported sequences, the system identifies nucleotide variants, determines the haplogroup, rules out possible pseudogene contamination, identifies novel DNA sequence variants, and evaluates the potential biological significance of each variant. This system should be beneficial for mtDNA analyses of biomedical physicians and investigators, population biologists and forensic scientists. MITOMASTER can be accessed at http://mammag.web.uci.edu/twiki/bin/view/Mitomaster.
Subject(s)
DNA, Mitochondrial/chemistry , Sequence Analysis, DNA/methods , Software , Algorithms , Animals , Computational Biology , Databases, Genetic , Genetic Variation , HumansABSTRACT
The MITOMAP (http://www.mitomap.org) data system for the human mitochondrial genome has been greatly enhanced by the addition of a navigable mutational mitochondrial DNA (mtDNA) phylogenetic tree of approximately 3000 mtDNA coding region sequences plus expanded pathogenic mutation tables and a nuclear-mtDNA pseudogene (NUMT) data base. The phylogeny reconstructs the entire mutational history of the human mtDNA, thus defining the mtDNA haplogroups and differentiating ancient from recent mtDNA mutations. Pathogenic mutations are classified by both genotype and phenotype, and the NUMT sequences permits detection of spurious inclusion of pseudogene variants during mutation analysis. These additions position MITOMAP for the implementation of our automated mtDNA sequence analysis system, Mitomaster.
Subject(s)
DNA, Mitochondrial/chemistry , Databases, Nucleic Acid , Mitochondrial Diseases/genetics , Mutation , DNA, Mitochondrial/classification , Genome , Humans , Internet , Phylogeny , Pseudogenes , User-Computer InterfaceABSTRACT
MITOMAP (http://www.MITOMAP.org), a database for the human mitochondrial genome, has grown rapidly in data content over the past several years as interest in the role of mitochondrial DNA (mtDNA) variation in human origins, forensics, degenerative diseases, cancer and aging has increased dramatically. To accommodate this information explosion, MITOMAP has implemented a new relational database and an improved search engine, and all programs have been rewritten. System administrative changes have been made to improve security and efficiency, and to make MITOMAP compatible with a new automatic mtDNA sequence analyzer known as Mitomaster.
