Analysis of Genomic and Proteomic Signals Using Signal Processing and Soft Computing Techniques

Bioinformatics is a data rich field which provides unique opportunities to use computational techniques to understand and organize information associated with biomolecules such as DNA, RNA, and Proteins. It involves in-depth study in the areas of genomics and proteomics and requires techniques from computer science,statistics and engineering to identify, model, extract features and to process data for analysis and interpretation of results in a biologically meaningful manner.In engineering methods the signal processing techniques such as transformation,filtering, pattern analysis and soft-computing techniques like multi layer perceptron(MLP) and radial basis function neural network (RBFNN) play vital role to effectively resolve many challenging issues associated with genomics and proteomics. In this dissertation, a sincere attempt has been made to investigate on some challenging problems of bioinformatics by employing some efficient signal and soft computing methods. Some of the specific issues, which have been attempted are protein coding region identification in DNA sequence, hot spot identification in protein, prediction of protein structural class and classification of microarray gene expression data. The dissertation presents some novel methods to measure and to extract features from the genomic sequences using time-frequency analysis and machine intelligence techniques.The problems investigated and the contribution made in the thesis are presented here in a concise manner. The S-transform, a powerful time-frequency representation technique, possesses superior property over the wavelet transform and short time Fourier transform as the exponential function is fixed with respect to time axis while the localizing scalable Gaussian window dilates and translates. The S-transform uses an analysis window whose width is decreasing with frequency providing a frequency dependent resolution. The invertible property of S-transform makes it suitable for time-band filtering application. Gene prediction and protein coding region identification have been always a challenging task in computational biology,especially in eukaryote genomes due to its complex structure. This issue is resolved using a S-transform based time-band filtering approach by localizing the period-3 property present in the DNA sequence which forms the basis for the identification.Similarly, hot spot identification in protein is a burning issue in protein science due to its importance in binding and interaction between proteins. A novel S-transform based time-frequency filtering approach is proposed for efficient identification of the hot spots. Prediction of structural class of protein has been a challenging problem in bioinformatics.A novel feature representation scheme is proposed to efficiently represent the protein, thereby improves the prediction accuracy. The high dimension and low sample size of microarray data lead to curse of dimensionality problem which affects the classification performance.In this dissertation an efficient hybrid feature extraction method is proposed to overcome the dimensionality issue and a RBFNN is introduced to efficiently classify the microarray samples

The Genome Sequence of the Grape Phylloxera Provides Insights into the Evolution, Adaptation, and Invasion Routes of an Iconic Pest

Background: Although native to North America, the invasion of the aphid-like grape phylloxera Daktulosphaira vitifoliae across the globe altered the course of grape cultivation. For the past 150 years, viticulture relied on grafting-resistant North American Vitis species as rootstocks, thereby limiting genetic stocks tolerant to other stressors such as pathogens and climate change. Limited understanding of the insect genetics resulted in successive outbreaks across the globe when rootstocks failed. Here we report the 294-Mb genome of D. vitifoliae as a basic tool to understand host plant manipulation, nutritional endosymbiosis, and enhance global viticulture. Results: Using a combination of genome, RNA, and population resequencing, we found grape phylloxera showed high duplication rates since its common ancestor with aphids, but similarity in most metabolic genes, despite lacking obligate nutritional symbioses and feeding from parenchyma. Similarly, no enrichment occurred in development genes in relation to viviparity. However, phylloxera evolved > 2700 unique genes that resemble putative effectors and are active during feeding. Population sequencing revealed the global invasion began from the upper Mississippi River in North America, spread to Europe and from there to the rest of the world. Conclusions: The grape phylloxera genome reveals genetic architecture relative to the evolution of nutritional endosymbiosis, viviparity, and herbivory. The extraordinary expansion in effector genes also suggests novel adaptations to plant feeding and how insects induce complex plant phenotypes, for instance galls. Finally, our understanding of the origin of this invasive species and its genome provide genetics resources to alleviate rootstock bottlenecks restricting the advancement of viticulture

Identification of ATP8A2 gene mutation in a consaguineous family segregating cerebellar atrophy and quadrupedal gait

Ankara : The Department of Molecular Biology and Genetics and the Graduate School of Engineering and Science of Bilkent University, 2012.Thesis (Ph. D.) -- Bilkent University, 2012.Includes bibliographical references leaves 138-153.Cerebellar ataxia, mental retardation, and dysequilibrium syndrome is a rare and heterogeneous neurodevelopmental disorder characterized by cerebellar atrophy, dysarthric speech, and quadrupedal locomotion. Here, a consanguineous family with four affected individuals which suggest an autosomal recessive inheritance was investigated. Homozygosity mapping analysis using high-resolution genotyping arrays in two affected individuals revealed four shared homozygous regions on 13q12, 19p13.3, 19q13.2, and 20q12. Target enrichment and next-generation sequencing of these regions in an affected individual was uncovered 11 novel protein altering variants which were filtered against dbSNP132 and 1000 genomes databases. Further population filtering using personal genome databases and previous exome sequencing datasets, segregation analysis, geographically-matched population screening, and prediction approaches revealed a novel missense mutation, p.I376M, in ATP8A2 segregated with the phenotype in the family. The mutation resides in a highly conserved C-terminal transmembrane region of E1-E2 ATPase domain. ATP8A2 is mainly expressed in brain, in particular with the highest levels at cerebellum which is a crucial organ for motor coordination. Mice deficient with Atp8a2 revealed impaired axonal transport in the motor neurons associated with severe cerebellar ataxia and body tremors. Recently, an unrelated individual with a de novo t(10;13) balanced translocation whose one of the ATP8A2 allele was disrupted has been identified. This patient shares similar neurological phenotypes including severe mental retardation and hypotonia. These findings suggest a role for ATP8A2 in the neurodevelopment, especially in the development of cerebro-cerebellar structures required for posture and gait in humans.Onat, Onur EmrePh.D